1 00:00:02,111 --> 00:00:03,846 Kara, how are you this morning? 2 00:00:04,084 --> 00:00:04,738 I'm good. 3 00:00:04,738 --> 00:00:05,817 How are doing Ted? 4 00:00:05,817 --> 00:00:08,879 I'm doing great, doing great. 5 00:00:08,879 --> 00:00:20,828 You and I were, I saw a thread on LinkedIn about some open source data and you had made a comment in there that opened my eyes to some things that I didn't know. 6 00:00:20,949 --> 00:00:32,787 So you and I jumped on a call, you educated me a little bit and um I think we have a really interesting conversation to be had because I can tell, I see that post. 7 00:00:33,437 --> 00:00:42,843 a million times and I think a lot of people don't understand all the details and nuance behind it and yeah, it'll be good to kind of get some clarity around that. 8 00:00:42,843 --> 00:00:46,695 um But before we do, let's get you introduced. 9 00:00:46,695 --> 00:00:50,948 So you and I were actually on a podcast together. 10 00:00:50,948 --> 00:00:53,189 Was that a year ago or two years ago? 11 00:00:53,486 --> 00:00:54,786 Yeah, let's see. 12 00:00:54,786 --> 00:00:59,286 We, we launched like two years ago, so it has to have been within the past two year window. 13 00:00:59,286 --> 00:01:00,786 I just can't remember when. 14 00:01:00,786 --> 00:01:01,521 Yeah. 15 00:01:01,521 --> 00:01:09,838 and I think Horace and Max from Lagora and um maybe the guy from LegalOn. 16 00:01:09,838 --> 00:01:16,404 um But anyway, so you are the co-founder of Describe AI. 17 00:01:16,404 --> 00:01:19,966 You have a A to J focus. 18 00:01:19,966 --> 00:01:23,309 um You actually host a podcast yourself. 19 00:01:23,309 --> 00:01:28,133 Why don't you kind of in the gaps there and tell us a little bit about 20 00:01:28,137 --> 00:01:30,468 who you are, what you do, and where you do it. 21 00:01:31,160 --> 00:01:31,500 Sure. 22 00:01:31,500 --> 00:01:31,940 Yeah. 23 00:01:31,940 --> 00:01:32,581 Thanks so much. 24 00:01:32,581 --> 00:01:34,211 It's really exciting to be on your show. 25 00:01:34,211 --> 00:01:35,122 That was a fun one. 26 00:01:35,122 --> 00:01:35,622 remember that. 27 00:01:35,622 --> 00:01:37,232 Horace always does a great show too. 28 00:01:37,232 --> 00:01:38,733 So that's a good one. 29 00:01:38,733 --> 00:01:39,513 Yeah, he does. 30 00:01:39,513 --> 00:01:42,365 um I'm, Cara Peterson. 31 00:01:42,365 --> 00:01:53,499 So I'm the co-founder of Describe AI and we are a two-year-old legal research company that em we like to think of ourselves sort of as the mavericks of legal research. 32 00:01:53,499 --> 00:01:58,741 So we've been called, some have called us the Robin Hood of legal research, which is a fun one too. 33 00:01:58,741 --> 00:02:00,610 But our, um 34 00:02:00,610 --> 00:02:11,421 whole goal is to really try to create tools that help um change the way people can access what should be, at least in theory, somewhat public information. 35 00:02:11,421 --> 00:02:14,884 So that's why I think that post was so interesting to me. 36 00:02:14,884 --> 00:02:25,214 And so as I've gotten really interested in AI over the past couple of years and sort of all the things that it can do to change so many different parts of our society. 37 00:02:25,230 --> 00:02:27,281 That's where the show came in that I started. 38 00:02:27,281 --> 00:02:29,132 called Building AI Boston. 39 00:02:29,132 --> 00:02:34,613 And that's all about how AI is being used by real people to do really interesting things. 40 00:02:34,613 --> 00:02:39,015 So it's beyond legal tech, but legal tech does pop up here and there. 41 00:02:39,015 --> 00:02:40,555 So that's me. 42 00:02:40,676 --> 00:02:41,836 Those are my two hats. 43 00:02:41,836 --> 00:02:46,257 And then my third hat is I have a real job that pays me, but we'll talk about that tomorrow. 44 00:02:46,623 --> 00:02:47,324 Okay. 45 00:02:47,324 --> 00:02:48,384 Good stuff. 46 00:02:48,384 --> 00:02:55,744 Well, let's, yeah, let's talk about this, this open source data movement, legal data movement and you know, what's reality? 47 00:02:55,744 --> 00:02:56,944 What's, what's hype? 48 00:02:56,944 --> 00:03:12,242 Um, I think it was kind of an interesting headline grabbing, um, post that talked about, you know, 99 % of case law was being open sourced and 49 00:03:12,242 --> 00:03:21,097 You you had chimed in with some interesting um comments just around kind of what that really means. 50 00:03:21,097 --> 00:03:26,560 It sounds like some of this data has actually been around for a long time, but might be somewhat dated. 51 00:03:26,560 --> 00:03:32,203 Like, of separate the fact and fiction around these recent announcements. 52 00:03:33,582 --> 00:03:34,322 Right, sure. 53 00:03:34,322 --> 00:03:39,042 So this was one of those things where I saw it come through my LinkedIn feed. 54 00:03:39,042 --> 00:03:43,502 sometimes you have those moments where you're like, should I jump on this one? 55 00:03:43,502 --> 00:03:44,202 Should I not? 56 00:03:44,202 --> 00:03:45,782 And so I kind of sat on it for a little bit. 57 00:03:45,782 --> 00:03:47,282 And then I decided, you know what? 58 00:03:47,282 --> 00:03:50,662 Yeah, I'm going to put in my two cents here. 59 00:03:50,742 --> 00:03:55,862 So the gist of it was when you think about case law. 60 00:03:55,862 --> 00:03:57,122 So that's what Describe has. 61 00:03:57,122 --> 00:03:59,982 have all kinds of case law right from across the country. 62 00:04:00,002 --> 00:04:02,542 And that is public information. 63 00:04:02,542 --> 00:04:02,982 Right? 64 00:04:02,982 --> 00:04:08,782 mean, so in theory, you should just be able to get whatever you need and get your access to that easily and so on and so forth. 65 00:04:08,782 --> 00:04:10,722 But we all know that's not the case. 66 00:04:10,922 --> 00:04:18,182 what we've done as a company is like find ways to get that case law and do things to it, which makes it more usable. 67 00:04:18,182 --> 00:04:22,922 But this post was really interesting to me because there's a few threads. 68 00:04:22,922 --> 00:04:29,774 One, and that I'm super in favor of is this open source kind of like making materials. 69 00:04:29,774 --> 00:04:35,254 available for people, although we have followed a slightly different path that describes it, which we can talk about later. 70 00:04:35,254 --> 00:04:41,114 And so what should be more available to people than our own laws, like, obviously. 71 00:04:41,134 --> 00:04:50,954 So this post was interesting because it was sort of presenting in some way that access to this case law unhugging face, which is great that they're doing this, that they're posting 72 00:04:50,954 --> 00:04:53,714 this, was somehow new and different. 73 00:04:53,914 --> 00:04:58,122 But anyone who's been around in this space for a while knows that this 74 00:04:58,122 --> 00:04:59,884 is not actually a new effort. 75 00:04:59,884 --> 00:05:04,788 And so I just wanted to jump in there and sort of talk about what's actually happening in that space. 76 00:05:04,788 --> 00:05:11,324 And then there was a second part about it that this was the reason I really jumped on it was that, oh, the case was there. 77 00:05:11,324 --> 00:05:21,994 So anyone can just throw an AI wrapper on it and make some tools that can compete with all the established legal research tools, which that's the part where I'm like, no, no, no, we 78 00:05:21,994 --> 00:05:24,206 need to talk about this. 79 00:05:24,220 --> 00:05:33,433 Yeah, I mean, there are multi-billion dollar companies that have built themselves on legal research, TR, Lexis, Bloomberg, others. 80 00:05:33,534 --> 00:05:37,459 And yeah, if it were just that simple, they'd be out of business. 81 00:05:37,459 --> 00:05:38,581 why is it? 82 00:05:38,581 --> 00:05:40,663 Tell us why it's not that simple. 83 00:05:41,314 --> 00:05:50,770 Right, so you can, anyone could get access, you know, and for first I should just say as a disclaimer, I am the sort of marketing business development side of our company. 84 00:05:50,770 --> 00:05:56,444 We have obviously another side that's the tech side, my co-founder Richard DeBona. 85 00:05:56,444 --> 00:06:00,067 So when I talk about this, I'm talking about it from more like the business perspective. 86 00:06:00,067 --> 00:06:04,390 He has much more, you know, deep thinking about how the tech actually works. 87 00:06:04,390 --> 00:06:08,973 But the point is, is just because it's there doesn't mean you can make it useful, right? 88 00:06:08,973 --> 00:06:10,786 You still need to be able to 89 00:06:10,786 --> 00:06:20,281 build tools with AI and with other types of technologies to mine the information that's useful for the user of that data. 90 00:06:20,281 --> 00:06:21,632 So it's very easy. 91 00:06:21,632 --> 00:06:32,878 as we've seen, people who are going directly into things like ChachiBT or whatnot to do legal research or legal um work are coming across. 92 00:06:32,878 --> 00:06:38,198 very significant problems that that data set will have for them, including hallucinations and things like that. 93 00:06:38,198 --> 00:06:41,258 So it was vastly oversimplifying. 94 00:06:41,258 --> 00:06:42,818 And again, it's just someone's post. 95 00:06:42,818 --> 00:06:52,638 It's not like, you know, they were writing a white paper or something, but just to vastly oversimplify that people can grab that data, take some kind of chat GPT wrapper, throw it 96 00:06:52,638 --> 00:07:02,298 on there, and you're going to create a tool that's helpful for people and furthering sort of access to the law or access to justice or the democratization of this information was 97 00:07:02,420 --> 00:07:08,797 so misleading and so many people were jumping on that post and saying, wow, this is game changing. 98 00:07:08,797 --> 00:07:09,909 It's gonna change everything. 99 00:07:09,909 --> 00:07:12,541 It just rubbed me the wrong way. 100 00:07:12,942 --> 00:07:16,754 Cause that it'll cause more harm than good if people think that's the result. 101 00:07:16,754 --> 00:07:19,466 Yeah, you know, I see it all the time. 102 00:07:19,466 --> 00:07:21,964 In fact, there's a guy I follow. 103 00:07:21,964 --> 00:07:28,091 I won't say his name, but he's a, he has really great content around AI use cases. 104 00:07:28,091 --> 00:07:35,275 And yesterday he posted that he just replaced his lawyer with this prompt. 105 00:07:35,275 --> 00:07:40,998 And you know, it looks, it's a, it's a great prompt, but there's, it's just not that simple. 106 00:07:40,998 --> 00:07:44,100 And I am definitely in the camp of. 107 00:07:44,167 --> 00:07:50,520 AI today, the general models can drastically reduce the amount of legal spend. 108 00:07:50,520 --> 00:07:54,042 Um, but it does not eliminate the need for lawyers. 109 00:07:54,042 --> 00:08:05,808 Like I gave you some examples, like we have, um, we have a four nine a program here, which is like a, a way that we incent, certain people on the team with like shadow equity in the 110 00:08:05,808 --> 00:08:06,748 company. 111 00:08:06,949 --> 00:08:13,522 And, we start, we started this program before AI existed. 112 00:08:13,522 --> 00:08:14,068 Well, 113 00:08:14,068 --> 00:08:22,187 before November of 2022 when, you know, chat GPT-35 was released, before it was easily accessible. 114 00:08:22,187 --> 00:08:29,488 So I just for the hell of it decided to upload our docs into chat GPT. 115 00:08:29,488 --> 00:08:31,068 Actually, I used Grok for that one. 116 00:08:31,068 --> 00:08:37,828 I've been playing around with Grok and asked for, are there any irregularities or risks associated with how we've implemented this program? 117 00:08:37,828 --> 00:08:42,528 And then I said, give me a risk ranking. 118 00:08:42,704 --> 00:08:46,948 and a probability that one of these risks could potentially materialize. 119 00:08:46,948 --> 00:08:48,730 And it did a fantastic job. 120 00:08:48,730 --> 00:08:52,353 And then I took that to our lawyers, and then we had a conversation about it. 121 00:08:52,353 --> 00:09:00,059 um So it doesn't eliminate the need for lawyers, but it can today, the general model is not a legal specific tool. 122 00:09:01,401 --> 00:09:05,605 There are some really valuable use cases, especially for small businesses like ours. 123 00:09:05,605 --> 00:09:09,330 We're like 43 people, and um we don't have 124 00:09:09,330 --> 00:09:10,891 big legal budgets. 125 00:09:10,891 --> 00:09:16,163 it's a good way for us to just do sanity checks, um especially on lower risk stuff. 126 00:09:16,163 --> 00:09:18,503 Like I don't even read NDAs anymore. 127 00:09:18,564 --> 00:09:26,157 You know, I will, if they, if they send me an NDA, I have a, I have a custom GPT that I've trained and say, Hey, what's the Delta? 128 00:09:26,157 --> 00:09:27,888 Are there any, is this one sided? 129 00:09:27,888 --> 00:09:30,298 Have a little prompt that I use takes me there. 130 00:09:30,298 --> 00:09:31,609 They're low risk. 131 00:09:31,609 --> 00:09:37,391 So, um, for high risk stuff, obviously lawyers still need to be involved in the real nuanced. 132 00:09:37,391 --> 00:09:39,465 Um, but 133 00:09:39,465 --> 00:09:49,693 What, you know, your comment about, yeah, you can't just throw chachi BT point chachi BT at these big expansive data sources for a number of reasons. 134 00:09:49,693 --> 00:10:04,125 mean, one, the context window issue, like even I think Gemini that I think is now at a million tokens, it gets all sorts of detail gets lost in the middle when you upload a ton 135 00:10:04,125 --> 00:10:08,488 of content and try to do retrieval or 136 00:10:08,698 --> 00:10:12,315 summarize it misses things today's tech does. 137 00:10:12,315 --> 00:10:16,663 What are some other challenges with just pointing it at a big data source? 138 00:10:16,663 --> 00:10:21,972 I don't mean from a technical perspective, but you know, just kind of data wise, what are the issues? 139 00:10:22,156 --> 00:10:28,139 Well, and I think your point about the nuance is really important and also your point about risk, right? 140 00:10:28,139 --> 00:10:37,034 So if you think about when you're in a situation, like think about it from the consumer of legal information or legal services point of view, right? 141 00:10:37,034 --> 00:10:38,195 So the client point of view. 142 00:10:38,195 --> 00:10:47,150 So most likely if you're engaging in some kind of legal dispute or legal situation, you have a pretty serious thing that you're trying to work through, right? 143 00:10:47,150 --> 00:10:51,682 So for, when you talk about the risk profile of something being wrong, 144 00:10:51,828 --> 00:11:03,351 it's much scarier how it could affect people's lives in a legal sphere or a medical sphere or something like that versus apartment hunting or planning a trip or things like that. 145 00:11:03,351 --> 00:11:09,343 And now this is all coming from someone who's very AI positive and very much a pro AI. 146 00:11:09,343 --> 00:11:11,250 I obviously I have show about it. 147 00:11:11,250 --> 00:11:12,164 I have a company about it. 148 00:11:12,164 --> 00:11:19,346 So I'm super, super uh excited about the potential the same way you are about how it can help humans become better at what they're doing. 149 00:11:19,346 --> 00:11:20,642 But I do think 150 00:11:20,642 --> 00:11:32,893 the biggest risk I see about this idea of just pointing at all this data, having people who frankly don't have the depth of knowledge either in the legal sphere and the tech 151 00:11:32,893 --> 00:11:35,555 sphere to understand what's coming back. 152 00:11:35,555 --> 00:11:36,115 Is it good? 153 00:11:36,115 --> 00:11:36,486 it bad? 154 00:11:36,486 --> 00:11:37,577 I mean, this is really hard. 155 00:11:37,577 --> 00:11:38,788 Benchmarking is really hard. 156 00:11:38,788 --> 00:11:39,959 We can talk about that too. 157 00:11:39,959 --> 00:11:44,076 em Because we could end up as a community. 158 00:11:44,076 --> 00:11:49,099 destroying any possibility we have of having these two will be helpful before they even get out of the gate. 159 00:11:49,099 --> 00:12:00,324 And so I'm probably not surprising anybody listening to this call that the judiciary um is not necessarily or the people involved in the courts and things of that nature aren't 160 00:12:00,324 --> 00:12:03,876 necessarily the most technically advanced people on earth, know, right? 161 00:12:04,157 --> 00:12:06,238 They just are and it's okay. 162 00:12:06,238 --> 00:12:09,140 And um that's not necessarily their job. 163 00:12:09,140 --> 00:12:14,122 But if you can see, and we saw it with hallucinations, if we create 164 00:12:14,270 --> 00:12:26,319 noise and we create situations where people are causing themselves, like we said, or the system more harm than good, we could end up getting shut down, you know, regulated to a 165 00:12:26,319 --> 00:12:31,802 point where we're actually hurting the long-term goals of what AI could do. 166 00:12:32,050 --> 00:12:42,870 and this, now I'm going to sound a little bit, a little bit uh soapboxy here, but some of this can come to the point of everyone's trying to make their dollar. 167 00:12:43,060 --> 00:12:43,612 on these tools. 168 00:12:43,612 --> 00:12:49,596 And of course I am too, so I'm not criticizing, but you know, it's a very different space when you're in the legal space. 169 00:12:49,596 --> 00:12:50,117 Yeah. 170 00:12:50,117 --> 00:12:52,039 Well, you mentioned benchmarking. 171 00:12:52,039 --> 00:12:55,143 What are your thoughts around that? 172 00:12:55,842 --> 00:12:57,583 Yeah, so benchmarking. 173 00:12:57,583 --> 00:13:00,744 So some of this is I come at it like I'm not an attorney. 174 00:13:00,744 --> 00:13:03,095 uh I don't have a legal background. 175 00:13:03,095 --> 00:13:07,607 have, like I said, a marketing, public health, of like social justice background, right? 176 00:13:07,607 --> 00:13:11,109 um But what do I know about these things, you know? 177 00:13:11,109 --> 00:13:22,828 And so when you think about legal tech as a field, as an ecosystem, you know, we haven't done a very good job of helping people assess what tools are good. 178 00:13:22,828 --> 00:13:29,324 what tools aren't good, what tools might work for them, which tools have the better housekeeping, know, seal approval. 179 00:13:29,384 --> 00:13:37,992 And I know there's a lot of discussion going on around this, particularly in the academic circles and with the legal librarians who are the people who probably will solve this for 180 00:13:37,992 --> 00:13:40,074 us eventually, which is great. 181 00:13:40,535 --> 00:13:45,329 But we're not giving consumers a very easy way to understand what's good and what's not. 182 00:13:45,329 --> 00:13:46,911 And again, I'm part of this. 183 00:13:46,911 --> 00:13:48,482 I'm not, you know, 184 00:13:48,482 --> 00:13:52,964 blaming others and saying we're perfect, but we tend to say, my product is good, trust me. 185 00:13:52,964 --> 00:13:57,066 And I'm patting my back for the people who are just watching, listening and not watching. 186 00:13:57,066 --> 00:14:06,531 em And that's not going to be enough for something like this because again, the consequences are too dire for people getting incorrect information. 187 00:14:06,531 --> 00:14:12,334 that's where the whole, excuse me, the whole human in the loop thing becomes very, very, very important. 188 00:14:12,348 --> 00:14:15,382 Yeah, and you know, I have seen some initiatives. 189 00:14:15,382 --> 00:14:20,353 It's been a while that probably Gosh, maybe close to a year ago. 190 00:14:20,353 --> 00:14:24,448 I heard about a uh consortium of 191 00:14:24,624 --> 00:14:27,145 sorts that had kind of gotten together. 192 00:14:27,145 --> 00:14:31,547 Harvey was on that list as participants, which I thought was interesting. 193 00:14:31,547 --> 00:14:38,810 I'm not sure how much vendors should play a role, maybe an advisory role, but I don't, you know, it's kind of like the Fox garden, the hen house. 194 00:14:38,810 --> 00:14:43,412 If the Pete, you creating your own, you grading your own tests. 195 00:14:43,412 --> 00:14:54,546 Um, we've seen gaming in, I mean, meta got slapped around pretty hard, not long ago with llama four and the, um, 196 00:14:54,546 --> 00:15:06,030 model that was released had material differences in benchmarking scores than what they presented during those benchmarking tests. 197 00:15:06,030 --> 00:15:14,800 yeah, think vendors should play a role, you know, feels like, I don't know, somebody else should be leading that effort with us supporting them. 198 00:15:15,327 --> 00:15:15,717 Agree. 199 00:15:15,717 --> 00:15:17,088 And it needs to be independent. 200 00:15:17,088 --> 00:15:22,211 And this is why I'm really in favor of it coming out of educational institutions. 201 00:15:22,211 --> 00:15:25,012 uh I worked in higher education for a long time. 202 00:15:25,012 --> 00:15:31,096 So I know that that's probably the best that we have for an independent lens. 203 00:15:31,096 --> 00:15:36,138 Excuse me, because um these firms that are marketing firms for legal tech are great. 204 00:15:36,139 --> 00:15:42,094 And, of course, they're going to do thorough, you know, sort of 205 00:15:42,094 --> 00:15:52,334 looking at these tools, but if it's a client or if it's a tool that is using their services, it's still hard for people to feel that it's completely independent. 206 00:15:52,334 --> 00:15:57,354 And I don't think in the current environment, the government is going to be doing anything about this. 207 00:15:57,374 --> 00:16:01,594 We couldn't really ask OpenAI or the other models to test it either. 208 00:16:01,594 --> 00:16:02,794 So it's a tough one. 209 00:16:02,794 --> 00:16:03,674 I don't know. 210 00:16:03,674 --> 00:16:09,834 And it's not regulated the way medical information or things like that is in some ways. 211 00:16:10,794 --> 00:16:22,622 I would say if there's anyone out there uh who wants to do this, I think you have a big wide open field and I think you should make the legal tech companies pay you for it and 212 00:16:22,622 --> 00:16:23,388 support it. 213 00:16:23,388 --> 00:16:24,989 Yeah, I agree. 214 00:16:24,989 --> 00:16:28,991 Now back to the kind of legal data movement. 215 00:16:28,991 --> 00:16:43,329 um You had, when you and I talked last, you had shared some interesting information on just kind of the history of the legal data liberation efforts, you know, in the Harvard 216 00:16:43,329 --> 00:16:46,561 case law project and the uh free law project. 217 00:16:46,561 --> 00:16:53,256 give, give our listeners a little bit of a perspective on where we've been and kind of 218 00:16:53,256 --> 00:16:54,607 where we are now. 219 00:16:55,438 --> 00:16:56,438 Right. 220 00:16:56,458 --> 00:17:05,098 So, and I'm sure there's things I don't know about, so I'll tell you the things I know, and then folks can put chime in in the comments about things they know too. 221 00:17:05,178 --> 00:17:10,978 So the first place that we came across is we were looking for case law ourselves a couple of years ago. 222 00:17:10,978 --> 00:17:13,738 The first place we found, you know, good access. 223 00:17:13,738 --> 00:17:22,478 And then there's also the idea of access to users to research and the access to people who want to use that technology to create a product, right? 224 00:17:22,478 --> 00:17:25,658 Or that, excuse me, that information to create a product, which are not the same. 225 00:17:26,638 --> 00:17:34,938 So the case law access project, which was out of the Harvard Law School's library, was a very interesting project that we came across. 226 00:17:34,938 --> 00:17:36,958 And they had all the case law. 227 00:17:36,958 --> 00:17:38,498 They have a wonderful story. 228 00:17:38,498 --> 00:17:42,118 Adam Ziegler could come on and talk about it if you want, I'm sure. 229 00:17:42,118 --> 00:17:43,658 Although you probably have to ask him. 230 00:17:43,658 --> 00:17:44,918 I'm not his rep. 231 00:17:45,038 --> 00:17:49,438 Where they went into the library and they quite literally scanned all their books. 232 00:17:49,438 --> 00:17:55,466 And there's just a fascinating story about how they had to break the bindings and the librarians were like, ah. 233 00:17:55,466 --> 00:17:56,306 some of these old books. 234 00:17:56,306 --> 00:18:06,651 anyway, so they scanned everything they had and they collaborated with a legal tech company that I'm forgetting the name right now, but um they uh worked with them. 235 00:18:06,651 --> 00:18:09,793 And then I think that company was sold to one of the big ones. 236 00:18:09,793 --> 00:18:13,934 I think it was Lexis, but may want to fact check me on that. 237 00:18:13,934 --> 00:18:21,318 So their data we noticed stopped around 2017 because that's when the project ended. 238 00:18:21,318 --> 00:18:21,954 So 239 00:18:21,954 --> 00:18:29,130 we had to look for another resource, but that was kind of like the original free the law group from what I've been able to see. 240 00:18:29,130 --> 00:18:30,701 And they're still doing a lot of really cool stuff. 241 00:18:30,701 --> 00:18:33,223 think they're ramping up again. 242 00:18:33,684 --> 00:18:44,613 So then we came across a uh group out in Ottawa, California that is powering a ton of innovation in this ecosystem and should be getting a lot of credit. 243 00:18:44,613 --> 00:18:51,052 And that was one of the other reasons I jumped on that post is because I'm like, hey, free law has been doing this for years. 244 00:18:51,052 --> 00:19:01,908 So the free lab project is, I think they've been around about 10 years and their sole purpose is to make sure that um things like case law and other things are actually 245 00:19:01,908 --> 00:19:03,919 accessible by regular people. 246 00:19:03,919 --> 00:19:10,463 And then they also have, you can create a commercial agreement with them where you ingest their data, which is how we get our data. 247 00:19:10,463 --> 00:19:11,304 So it's great. 248 00:19:11,304 --> 00:19:13,015 And that's a commercial license. 249 00:19:13,015 --> 00:19:14,235 So they're doing that. 250 00:19:14,235 --> 00:19:19,018 um And then a very interesting space that's new and 251 00:19:19,520 --> 00:19:26,913 I think there's a lot of cool things happening here, including at Describe, has to do with sort of the other parts of the law. 252 00:19:26,913 --> 00:19:29,274 Case law is one part of the law. 253 00:19:29,394 --> 00:19:34,766 But a lot of people think of statutes, regulations, and all that other stuff as the real law. 254 00:19:34,766 --> 00:19:39,282 So happy to talk about that, because that's a big missing piece of the puzzle right now. 255 00:19:39,282 --> 00:19:42,668 Yeah, well, let's uh share your thoughts on that. 256 00:19:43,374 --> 00:19:54,914 Yeah, so again, coming from a non-lawyer, so forgive me if I'm not explaining this the way a professor would in law school, but certainly case law is part of what lawyers, attorneys 257 00:19:54,914 --> 00:19:58,534 have to look at as they're building a case or writing a brief or doing things like that. 258 00:19:58,534 --> 00:20:05,254 But of course, much of the law is done with just the law of the land, which statutes, regulations, things of that nature. 259 00:20:05,254 --> 00:20:08,914 And it's really, really hard to get. 260 00:20:09,014 --> 00:20:13,100 It's almost impossible to get, and that's weird. 261 00:20:13,100 --> 00:20:15,802 right, when you think about it, because it's all public information. 262 00:20:15,802 --> 00:20:24,258 And this also, I think, links back to the judiciary in many states, state governments, and things like that don't necessarily have very sophisticated technology. 263 00:20:24,258 --> 00:20:27,320 They can't, you know, it's not something they've invested in. 264 00:20:27,320 --> 00:20:31,103 There are sort of workarounds that other companies have provided to them to make it easier for them. 265 00:20:31,103 --> 00:20:33,044 And then that data is sort of blocked away. 266 00:20:33,044 --> 00:20:40,649 m So uh some companies or some places have started to look at pulling that data directly. 267 00:20:40,649 --> 00:20:42,110 And that is 268 00:20:42,110 --> 00:20:42,600 what we're doing. 269 00:20:42,600 --> 00:20:49,672 So we had looked in because we really need to add those resources to our database for it to be as broad as possible. 270 00:20:49,672 --> 00:20:55,374 em And we started to look at where we could get that data without having to go get it ourselves. 271 00:20:55,374 --> 00:21:05,167 And I think we were quoted by one group who shall remain anonymous, $100,000 just for some small piece of this data. 272 00:21:05,167 --> 00:21:06,717 And so we thought this is absurd. 273 00:21:06,717 --> 00:21:09,476 You know, so 274 00:21:09,656 --> 00:21:10,726 We're getting it ourselves. 275 00:21:10,726 --> 00:21:18,528 So we're going to have every single piece of, tell you the list because I want to make sure I get this right. 276 00:21:18,528 --> 00:21:25,590 Statutes, regulations, state constitutions, court rules, session laws, and attorney general opinions from all 50 states. 277 00:21:25,669 --> 00:21:28,051 And it will be part of our database. 278 00:21:28,051 --> 00:21:30,182 We will be demoing this at Ilticon. 279 00:21:30,182 --> 00:21:31,532 So come by and see it. 280 00:21:31,532 --> 00:21:37,294 But we think we'll have the most thorough corpus of anyone, especially at the prices we charge. 281 00:21:37,294 --> 00:21:39,233 And everything will be fully searchable. 282 00:21:39,233 --> 00:21:40,283 by natural. 283 00:21:40,584 --> 00:21:41,034 Wow. 284 00:21:41,034 --> 00:21:42,675 Yeah, that's big news. 285 00:21:42,675 --> 00:21:44,568 Yeah, that's big news. 286 00:21:44,568 --> 00:21:54,198 we are em recording on Monday the 4th, but this episode will be released on Wednesday the 6th, which is going to be in time for Ilticon so folks can come by. 287 00:21:54,198 --> 00:21:55,719 Are you guys exhibiting? 288 00:21:56,155 --> 00:21:58,476 Yeah, we're in the startup hub, which is cool. 289 00:21:58,476 --> 00:22:00,597 haven't been to Ilticon before. 290 00:22:00,597 --> 00:22:05,460 The only conference we've done before is Tech Show, which was so much fun. 291 00:22:05,460 --> 00:22:06,300 my gosh. 292 00:22:06,300 --> 00:22:09,412 We love that one with Bob Ambrosio and the Startup Alley and stuff. 293 00:22:09,412 --> 00:22:11,833 So anyone out there who's got a startup apply for that. 294 00:22:11,833 --> 00:22:13,964 It's so much fun if you can get it. 295 00:22:14,204 --> 00:22:17,236 So yeah, so we're in booth one, two, three in the Startup Alley. 296 00:22:17,236 --> 00:22:18,532 So come see us. 297 00:22:18,532 --> 00:22:19,002 Awesome. 298 00:22:19,002 --> 00:22:30,259 Yeah, we did when we were first finding our way in legal back in our predecessor company, we were called Acrowire and I'm a former Microsoft guy and just kind of started consulting 299 00:22:30,259 --> 00:22:32,900 on the side as a lot of tech people do. 300 00:22:32,900 --> 00:22:36,212 And then the side gig started making more than the day job. 301 00:22:36,212 --> 00:22:39,284 So I quit and uh terrible timing. 302 00:22:39,284 --> 00:22:47,108 This was like right after the financial crisis, but I had enough client work to keep me busy and my bait, my bills paid. 303 00:22:47,260 --> 00:23:00,065 So I jumped in and we fell down the legal rabbit hole early and we didn't really know where our skills mapped on the, on the kind of the market spectrum in terms of size. 304 00:23:00,065 --> 00:23:13,411 we are our first show was like ABA tech show and it's great for kind of solo and small firms, but for big firms really ill to legal week, those are, those are better fits for, 305 00:23:13,411 --> 00:23:15,852 for our audience, which is, which is large law. 306 00:23:15,852 --> 00:23:17,270 Um, 307 00:23:17,270 --> 00:23:21,922 our first experience in legal tech was just a few months after launching. 308 00:23:21,922 --> 00:23:28,715 We were uh a finalist for one of the legal week awards. 309 00:23:28,955 --> 00:23:30,836 Wow, that was amazing. 310 00:23:30,836 --> 00:23:33,087 Cause we had never been to anything like that. 311 00:23:33,087 --> 00:23:41,360 And then to walk into that venue down there at the Hyatt, I thought the Hilton, the Hilton in New York, was like, holy smokes. 312 00:23:41,360 --> 00:23:43,932 Like this is, this is big time. 313 00:23:43,932 --> 00:23:45,117 It was pretty cool. 314 00:23:45,117 --> 00:23:45,709 Yeah. 315 00:23:45,709 --> 00:23:47,663 that was back when Stephanie Wilkins was running it. 316 00:23:47,663 --> 00:23:48,253 was awesome. 317 00:23:48,253 --> 00:23:49,193 Yeah. 318 00:23:49,193 --> 00:23:49,654 Yeah. 319 00:23:49,654 --> 00:23:52,094 mean, legal week is an interesting one for us. 320 00:23:52,094 --> 00:24:03,359 We, we attend every year, but it, you know, historically has been e-discovery focused and I, you know, I know they've tried to move beyond that in recent years, but we go, we 321 00:24:03,359 --> 00:24:04,699 don't, we don't exhibit. 322 00:24:04,699 --> 00:24:09,741 Um, the exhibit hall is very disjointed. 323 00:24:09,741 --> 00:24:17,584 Um, like, you know, it's, there's all little sorts of nooks and crannies and, um but we always make an appearance at legal week. 324 00:24:18,385 --> 00:24:19,204 for 325 00:24:19,367 --> 00:24:20,097 it's a good one. 326 00:24:20,097 --> 00:24:30,606 And then the one that I really liked a lot was very different, completely at other end of the scale, which is the LSC ITC, which is the Legal Services Council, right? 327 00:24:30,606 --> 00:24:34,089 So that was all about access to justice stuff. 328 00:24:34,089 --> 00:24:35,220 So that was really cool. 329 00:24:35,220 --> 00:24:40,154 was kind of, Bob Brogy wrote a really interesting piece last year about it, about the difference. 330 00:24:40,154 --> 00:24:48,340 Like he went from one to the other and he was like, wow, just that shows the gulf in certain resources and the two ends of the... 331 00:24:48,366 --> 00:24:49,296 cool, so to speak. 332 00:24:49,296 --> 00:24:50,097 Interesting. 333 00:24:50,097 --> 00:24:51,958 Well, I'm curious. 334 00:24:51,958 --> 00:24:54,619 She had mentioned the group out of Oakland. 335 00:24:54,619 --> 00:24:57,300 Are they? 336 00:24:57,300 --> 00:24:57,551 Yeah. 337 00:24:57,551 --> 00:24:57,851 Yeah. 338 00:24:57,851 --> 00:25:01,703 So is that an academic institution? 339 00:25:01,703 --> 00:25:03,444 Like who's behind that? 340 00:25:03,798 --> 00:25:05,679 Yeah, so they're nonprofit. 341 00:25:05,679 --> 00:25:09,822 They're run by a guy named Michael Listener, who's great. 342 00:25:09,822 --> 00:25:11,262 So hi, Michael, if you're listening. 343 00:25:11,262 --> 00:25:15,785 um And they are, um like I say, they're a nonprofit. 344 00:25:15,785 --> 00:25:18,577 they are very mission driven. 345 00:25:18,577 --> 00:25:24,851 I'm sure that they've got all kinds of academics involved with them and sort of on their board and things like that. 346 00:25:24,851 --> 00:25:29,593 But they're a straight up nonprofit, which means that they are... 347 00:25:29,593 --> 00:25:31,174 ah 348 00:25:31,478 --> 00:25:35,183 sort of at the source powering a lot of the legal tech innovation. 349 00:25:35,183 --> 00:25:39,729 And of course, they're not going to say publicly who their clients are unless they're like us. 350 00:25:39,729 --> 00:25:42,142 And we're always willing to say we're their client. 351 00:25:42,142 --> 00:25:50,479 You would scratch the surface on a lot of these startups and you would see that's where their data is coming from, for sure. 352 00:25:50,479 --> 00:26:04,724 with these types of organizations out there working hard to kind of open source uh legal information, does that open the door to challenge, you know, what's largely a duopoly, 353 00:26:04,724 --> 00:26:10,859 feels like, with Westlaw and Lexis with solutions, does that open the door for that? 354 00:26:12,798 --> 00:26:13,279 Yes. 355 00:26:13,279 --> 00:26:13,629 Yes. 356 00:26:13,629 --> 00:26:16,060 So yes and no, depending on how you look at it. 357 00:26:16,060 --> 00:26:18,842 So broadly speaking, absolutely. 358 00:26:18,842 --> 00:26:20,943 Like for sure. 359 00:26:20,943 --> 00:26:29,568 Like if anything is going to challenge those duopolies and those extraordinarily powerful companies, it's AI. 360 00:26:29,568 --> 00:26:29,988 Right? 361 00:26:29,988 --> 00:26:38,182 mean, that is the moment is here, you and they know that and that's why they're building so fast and acquiring so quickly and you know, all this stuff. 362 00:26:38,182 --> 00:26:39,573 there's no question. 363 00:26:39,573 --> 00:26:39,873 Right. 364 00:26:39,873 --> 00:26:41,742 And we've seen some really interesting 365 00:26:41,742 --> 00:26:46,822 things happening like with Villex and Cleo and know, Harvey and Lexus. 366 00:26:46,822 --> 00:26:50,562 So everyone's paying attention to this, as you certainly know, right, Ted? 367 00:26:50,562 --> 00:26:53,542 Because you do, you're a podcast, you talk about this a lot. 368 00:26:54,442 --> 00:26:57,662 But where it also opens the door. 369 00:26:57,682 --> 00:26:59,342 So that's like one end of the market, right? 370 00:26:59,342 --> 00:27:08,322 So and a lot of people, if not almost all people are aiming for the exact same part of the market, right? 371 00:27:08,322 --> 00:27:10,782 So the well-served... 372 00:27:11,180 --> 00:27:13,072 the places and this is fine. 373 00:27:13,072 --> 00:27:14,122 They need their tools. 374 00:27:14,122 --> 00:27:14,563 This is great. 375 00:27:14,563 --> 00:27:16,274 I have nothing, no digs or anything. 376 00:27:16,274 --> 00:27:21,709 But if everybody's always aiming for the same part of the market, there's not going to be a lot of innovation, right? 377 00:27:21,709 --> 00:27:25,442 That's not where things are going to get exciting, at least from my point of view. 378 00:27:25,442 --> 00:27:32,968 My point of view and the way we focus at Describe is how about that gigantic, unserved market, right? 379 00:27:32,968 --> 00:27:37,590 And I think it was, I don't want to misquote him, but I'm pretty sure it was Jack Newton. 380 00:27:37,590 --> 00:27:40,984 It was Jack Newton from Clio who said, um 381 00:27:40,984 --> 00:27:47,218 that there was maybe, I think it was like a trillion dollars of unmet need in the legal services industry. 382 00:27:47,218 --> 00:27:58,166 Now we better fact check that or, you know, I might get a letter from Uncle Leo saying that was wrong, but regardless, there's an enormous amount of unmet need out there for 383 00:27:58,166 --> 00:28:00,148 legal services, legal information. 384 00:28:00,148 --> 00:28:06,512 So when we were first starting out, uh we thought to ourselves, we could be a nonprofit, right? 385 00:28:06,512 --> 00:28:09,806 We could probably be a very successful nonprofit. 386 00:28:09,806 --> 00:28:13,386 if we wanted to be, we could get grants, we could do all sorts of things. 387 00:28:13,386 --> 00:28:16,266 But we always said, nope, we're a business. 388 00:28:16,906 --> 00:28:17,626 We're a business. 389 00:28:17,626 --> 00:28:29,346 And while we have a mission-driven focus, we are trying to create a very successful and sustainable and profitable business because AI allows us to offer very high quality tools 390 00:28:29,346 --> 00:28:35,526 that you could have not even imagined just a few years ago could possibly exist without human intervention. 391 00:28:37,870 --> 00:28:45,087 put it out there at a price that is so absurdly low compared to the competitors that we're just gonna gobble up how much of market share. 392 00:28:45,087 --> 00:28:46,748 that's the goal. 393 00:28:46,748 --> 00:28:54,666 So while we do like to present ourselves and we are mission driven, we have a very serious market driven approach to what we're doing. 394 00:28:54,666 --> 00:29:00,231 um And it's really starting to come to fruition now that we have a paid tool. 395 00:29:00,231 --> 00:29:03,946 em So I think there's huge opportunity, but I think... 396 00:29:03,946 --> 00:29:15,923 I would caution other people who are looking at this space, don't automatically assume you have to compete, you know, with Harvey, with Lexus directly, with Vlex, you know, that's 397 00:29:15,923 --> 00:29:16,954 not easy, right? 398 00:29:16,954 --> 00:29:18,715 And they're, those are very well funded firms. 399 00:29:18,715 --> 00:29:24,148 So look at other parts of the market where other people aren't looking at it and see what you can do there. 400 00:29:24,424 --> 00:29:34,090 Yeah, you know, I candidly, I've talked about this publicly before and I don't know, it may ruffle some feathers, the, what, what? 401 00:29:34,090 --> 00:29:34,380 Yeah. 402 00:29:34,380 --> 00:29:36,001 I mean, I'm not for everybody. 403 00:29:36,001 --> 00:29:38,252 know that my opinions don't res. 404 00:29:38,792 --> 00:29:39,672 Yeah. 405 00:29:40,133 --> 00:29:40,563 Yeah. 406 00:29:40,563 --> 00:29:41,244 Feather ruffle it. 407 00:29:41,244 --> 00:29:41,444 Yeah. 408 00:29:41,444 --> 00:29:52,275 I've ruffled a few feathers, um, in my day and, um, not intentionally, but I feel like just being candid and if, you know, if people get offended, then they do, but 409 00:29:52,275 --> 00:29:56,788 You know, I, we have really struggled on the smaller end of the market with, within the law firm world. 410 00:29:56,788 --> 00:30:01,812 Um, a lot of people call mid-law like 50 to like 150 lawyers. 411 00:30:01,812 --> 00:30:04,573 That's that really feels like small law for us. 412 00:30:04,573 --> 00:30:08,096 So, um, our market is really a hundred attorneys and up. 413 00:30:08,096 --> 00:30:13,129 And there are about 400 of those law firms in North America, which is our focus. 414 00:30:13,129 --> 00:30:20,530 We're doing some business in the UK now too, but by my estimates and there's no good numbers, there's only about 600 law firms on planet earth. 415 00:30:20,530 --> 00:30:22,381 who have more than a hundred attorneys. 416 00:30:22,381 --> 00:30:35,304 There are tens of thousands, if not hundreds of thousands of solo and smaller firms in that it's a very kind of, um, I guess steeply sloping pyramid. 417 00:30:35,304 --> 00:30:38,625 Um, yeah, that's a good way to describe it. 418 00:30:38,625 --> 00:30:41,465 Um, but it's really hard to do business there. 419 00:30:41,566 --> 00:30:50,578 And the reason it's hard to do business there as a tech company is because law firms historically have not valued, not seen tech as strategic. 420 00:30:50,828 --> 00:30:56,110 Um, and, and, mean, that's just the fact, like people can say what they want. 421 00:30:56,110 --> 00:30:58,351 I've been in this space 20 years. 422 00:30:58,351 --> 00:31:04,874 I know it to be true that that has been the historical perspective in the law firm world that is changing. 423 00:31:04,874 --> 00:31:07,945 And there are, and there are outliers where that is not true. 424 00:31:07,945 --> 00:31:17,649 And I, and I get that, but in the smaller, in the smaller end of the market, the things that we've struggled with are, um, a lack of sophistication from a technical perspective, 425 00:31:17,649 --> 00:31:20,500 you know, they could be rock stars on the. 426 00:31:20,500 --> 00:31:32,643 practice side, but a lot of times in that hundred attorney and under world, you'll have an IT director who, um, Kate, who was a, their former network administrator did a good job. 427 00:31:32,643 --> 00:31:35,064 So they got reported and now they're, you know what I mean? 428 00:31:35,064 --> 00:31:39,685 And there's nothing wrong with that, but it's, it's we. 429 00:31:40,266 --> 00:31:40,776 Right. 430 00:31:40,776 --> 00:31:41,986 Yeah, exactly. 431 00:31:41,986 --> 00:31:48,711 And so there's just been a lack of technical sophistication and you know, there's also a lot of, I got to 432 00:31:48,711 --> 00:31:50,592 a really good friend of mine who here in St. 433 00:31:50,592 --> 00:31:54,855 Louis, he owns a 50 attorney law firm and we play golf together. 434 00:31:54,855 --> 00:32:06,493 you know, I had, he asked me for somebody to go speak at his retreat and I teed a couple of people up and he was complaining about the price. 435 00:32:06,493 --> 00:32:12,197 I'm like, dude, you are lucky that this person is even giving you their attention, right? 436 00:32:12,197 --> 00:32:16,460 They normally speak in front of hundreds of thousands of people. 437 00:32:16,476 --> 00:32:27,089 Like that's, that's a bargain, but you know, it's an all small businesses, including us, when you're every dollar matters, you got, really have to manage your spend. 438 00:32:27,089 --> 00:32:36,870 But when you have limited budget combined with an audience who doesn't see tech as strategic, it's a really difficult market to sell into as a tech company. 439 00:32:37,218 --> 00:32:42,502 completely, but those people are also in very serious peril. 440 00:32:42,923 --> 00:32:43,323 Right? 441 00:32:43,323 --> 00:32:45,665 Like, and we're talking like a long arc here. 442 00:32:45,665 --> 00:32:56,694 So you're right for like individual companies, like can, can potential customers adapt fast enough to keep us sustainable and keep us going like for sure, like on an individual 443 00:32:56,735 --> 00:33:03,340 or even like a market, like a current market level, like you could argue that the change is going to be too slow and all that. 444 00:33:03,340 --> 00:33:05,942 But if you look at like a broader arc, 445 00:33:06,286 --> 00:33:08,466 this is not going to stay the same. 446 00:33:08,466 --> 00:33:13,766 Like think about sort of how we get our medical care now, right? 447 00:33:13,766 --> 00:33:15,846 And how much that has changed. 448 00:33:15,846 --> 00:33:32,786 And if you had a doctor's office, say, who refused to do e-charts or refused to meet with you online or refused to take your prescriptions through the portal versus calling. 449 00:33:32,786 --> 00:33:35,724 it's just, and medical is another weird. 450 00:33:35,724 --> 00:33:41,108 you want to, but like people, couldn't survive, right? 451 00:33:41,108 --> 00:33:42,079 You couldn't survive. 452 00:33:42,079 --> 00:33:52,388 so law probably has the wrong impression that they don't, there's some people who think that they adapt, they don't have to adapt in the same way. 453 00:33:52,388 --> 00:33:53,609 And there's a lot of resistance. 454 00:33:53,609 --> 00:33:58,563 And, for sure, one of the dumb jokes we tell, and we have many, is that when we're like, what should we build? 455 00:33:58,563 --> 00:34:05,198 Let's find the uh part of the economy where people are most, you know, 456 00:34:05,198 --> 00:34:08,518 open to risk and they love technology and they just are ready to share. 457 00:34:08,518 --> 00:34:10,178 We're like, wow, perfect. 458 00:34:10,178 --> 00:34:12,298 know, talk about what could we have picked that was harder? 459 00:34:12,298 --> 00:34:13,918 I can't even imagine. 460 00:34:13,978 --> 00:34:19,658 But I do think we're at a point where no matter what it has to change. 461 00:34:19,658 --> 00:34:29,658 can't have the triangulation we have right now with the advent of AI and just how fundamentally that's going to change everything we do soup to nuts. 462 00:34:29,658 --> 00:34:30,018 Right. 463 00:34:30,018 --> 00:34:35,318 And then you have a vastly underserved part of the market. 464 00:34:35,648 --> 00:34:42,594 and then of extraordinarily overpriced legacy providers, like that's gonna implode, right? 465 00:34:42,594 --> 00:34:55,155 And so the smart attorneys out there, and they're all smart, no offense, the tech forward and the forward thinking attorneys are gonna have to figure out how to adapt to this or 466 00:34:55,155 --> 00:35:00,039 they're gonna see their share of the market, know, start to crater. 467 00:35:00,039 --> 00:35:03,372 And the new students who are going through law school and learning this stuff, 468 00:35:03,372 --> 00:35:05,267 are gonna come out with different expectations too. 469 00:35:05,267 --> 00:35:09,234 So there'll be a fight for talent as well. 470 00:35:09,234 --> 00:35:10,315 Yeah, no, for sure. 471 00:35:10,315 --> 00:35:16,989 Yeah, that kind of legacy mindset is incompatible with where we're going. 472 00:35:16,989 --> 00:35:25,075 It's just, I know so many firms that are going to struggle to adapt and not necessarily some small firms. 473 00:35:25,075 --> 00:35:30,838 I know of an Amlaw firm who I'm really good friends with, the chief knowledge officer there. 474 00:35:31,524 --> 00:35:32,940 And, um 475 00:35:33,402 --> 00:35:39,658 I was working on a project with her for a presentation and she was completely dark in January. 476 00:35:39,658 --> 00:35:41,066 And I was like, where have you been? 477 00:35:41,066 --> 00:35:42,851 She's like, I've been working on a DMS upgrade. 478 00:35:42,851 --> 00:35:44,103 I'm like, DMS? 479 00:35:44,103 --> 00:35:44,733 You've been working? 480 00:35:44,733 --> 00:35:46,035 I was like, that's IT. 481 00:35:46,035 --> 00:35:46,895 What's the chief knowledge? 482 00:35:46,895 --> 00:35:48,387 She's like, I am IT. 483 00:35:48,387 --> 00:35:49,407 And I am KM. 484 00:35:49,407 --> 00:35:56,875 And it's like, OK, your firm has set you up for failure if you're going to be promoting knowledge and innovation. 485 00:35:57,176 --> 00:35:57,474 Yeah. 486 00:35:57,474 --> 00:35:59,266 strategic error on their part. 487 00:35:59,266 --> 00:36:05,501 And you know, maybe this dovetails back to the conversation we were having about benchmarking too, right? 488 00:36:05,501 --> 00:36:13,102 Because the risks for firms too, and for, you know, uh any size firm is huge if they pick the wrong tool. 489 00:36:13,237 --> 00:36:23,305 It's huge if they rely on something that's spotty, you know, that's, and that's why the momentum is hard to change with the big trusted companies because I get it. 490 00:36:23,305 --> 00:36:24,470 I mean, if I'm... 491 00:36:24,470 --> 00:36:29,214 you know, working at some firm and I'm in charge of their IT and making sure they have the right tools. 492 00:36:29,214 --> 00:36:32,617 I'm not really interested in some, you know, brand new startup. 493 00:36:32,617 --> 00:36:34,769 Like that's, that's scary, right? 494 00:36:34,769 --> 00:36:36,400 That's, that's super scary. 495 00:36:36,400 --> 00:36:41,665 So again, there's a comeback to where, where can the industry provide a little more reassurance? 496 00:36:41,665 --> 00:36:43,516 I think it's useful for all of us. 497 00:36:43,516 --> 00:36:46,863 Yeah, well you've had some validation. 498 00:36:46,863 --> 00:36:52,694 talk a little bit about the case text and law school curricula and what you guys are doing there. 499 00:36:52,909 --> 00:36:54,610 Yeah, so this is really fun. 500 00:36:54,610 --> 00:36:58,430 this was this actually happened at the tech show. 501 00:36:58,970 --> 00:37:00,370 it's always good to self. 502 00:37:00,370 --> 00:37:04,550 It's always good to show up at these things when you're when you're new, because you never know who you're going to meet. 503 00:37:05,190 --> 00:37:08,530 So we, as folks know, have been listening. 504 00:37:08,530 --> 00:37:09,890 have case law research. 505 00:37:09,890 --> 00:37:16,530 It's we have free access and we have a paid tool, $10 a month and $20 a month, depending on the level. 506 00:37:16,530 --> 00:37:18,810 So paid, but almost free. 507 00:37:18,810 --> 00:37:19,510 Right. 508 00:37:19,510 --> 00:37:20,410 So 509 00:37:21,142 --> 00:37:29,889 The uh legal tech curriculum is from, hang on, I'm just gonna get the exact right terminology here so I'm not saying the wrong thing. 510 00:37:29,889 --> 00:37:43,008 So we will be rolling out into uh over 350 law schools uh internationally this fall as part of a legal curriculum that is from the National Society for Legal Technology and will 511 00:37:43,008 --> 00:37:45,379 be part of their legal research curriculum. 512 00:37:45,379 --> 00:37:49,442 And what's really fun about this is that we are replacing case text 513 00:37:49,502 --> 00:38:00,140 in their um curriculum because case tax no longer, now that they've been acquired for 650 million, you good for them, um they don't have free access any longer. 514 00:38:00,140 --> 00:38:02,192 I think that was turned off in March. 515 00:38:02,192 --> 00:38:06,405 So we will be replacing uh our friends at Case Tax in the curriculum. 516 00:38:06,405 --> 00:38:14,171 And so we will be included with Lexis Plus, Westlaw, Bloomberg Law, Fast Case, and HeinOnline, and us, and Describe. 517 00:38:14,171 --> 00:38:16,192 So it does show that 518 00:38:16,415 --> 00:38:18,846 I guess, uh validation of the tool. 519 00:38:18,846 --> 00:38:31,164 um Doug Lusk from the CEO from uh the, NSLT said, you know, we were his favorite and he was very impressed with what we were building. 520 00:38:31,164 --> 00:38:34,536 So that was some big validation for us. 521 00:38:34,536 --> 00:38:45,932 um Another nice piece of validation we had recently was Bob Enroji covered our AI citator release and said we were now poised to meaningfully 522 00:38:45,998 --> 00:38:50,741 uh be thought of as a competitor for the big legal research tools. 523 00:38:50,741 --> 00:38:52,112 So these are pretty exciting things. 524 00:38:52,112 --> 00:38:56,966 And again, good luck of having having done this without AI. 525 00:38:56,966 --> 00:38:59,608 It's quite literally would not have been possible. 526 00:38:59,608 --> 00:39:09,554 So we're kind of the poster child for what, how nimble and lean and sort of creative AI companies can be, which is pretty cool. 527 00:39:10,595 --> 00:39:11,536 Thank you. 528 00:39:11,536 --> 00:39:12,957 We're very excited. 529 00:39:14,098 --> 00:39:14,750 Yeah. 530 00:39:14,750 --> 00:39:17,180 So an interesting thing happened this week. 531 00:39:17,180 --> 00:39:19,671 So we are a TLTF portfolio company. 532 00:39:19,671 --> 00:39:28,753 um one of the directors over there tagged uh me and a few others in the post, Tom Baldwin from Ennegrata. 533 00:39:28,954 --> 00:39:37,296 And uh a VC had written a future of law um kind of 534 00:39:38,037 --> 00:39:40,157 Manifesto and it's so good. 535 00:39:40,157 --> 00:39:41,617 Like I, I agree. 536 00:39:41,617 --> 00:39:42,977 It's a, it's, they're called catalyst. 537 00:39:42,977 --> 00:39:45,637 I'd really, I'd never heard of them prior to that. 538 00:39:45,637 --> 00:39:53,457 Maybe we can create a link in the show notes, but they mentioned info dash and like as an, company they're excited about. 539 00:39:53,477 --> 00:40:00,893 Um, and I, know, I get like 15, I'm not exaggerating 15 to 20 emails from VCs a week. 540 00:40:00,893 --> 00:40:04,694 LinkedIn messages, they call, I don't know how they have my cell phone number, but they do. 541 00:40:04,694 --> 00:40:10,455 And it's, I'm flattered, but I could fill up my calendar with just talking to them and we don't need money. 542 00:40:10,455 --> 00:40:20,958 Like we're V we're, um, we're, bootstrapped and we took a little bit of funding from TLTF, not really for the funding, but just because the working with them is amazing. 543 00:40:20,958 --> 00:40:23,208 Um, they are. 544 00:40:23,208 --> 00:40:24,399 Yeah. 545 00:40:24,399 --> 00:40:25,759 They, they can open doors. 546 00:40:25,759 --> 00:40:26,859 They know the market. 547 00:40:26,859 --> 00:40:29,122 It's, it's a, it's a really good relationship. 548 00:40:29,122 --> 00:40:33,589 Plus you get to go to their fun summit, which is always in really cool places. 549 00:40:34,592 --> 00:40:35,592 Yeah. 550 00:40:36,255 --> 00:40:38,094 Oh, Austin's the best, yeah. 551 00:40:38,094 --> 00:40:42,755 in like the Ritz Carlton and Fort Lauderdale and then last year in Key Biscayne. 552 00:40:42,795 --> 00:40:43,706 So it's really good. 553 00:40:43,706 --> 00:40:56,419 But you know, like, I think what is also interesting now with in terms of challengers to these big established players is now you have funds like TLTF that are completely zeroed 554 00:40:56,419 --> 00:40:59,124 in and you know, reading that 555 00:40:59,124 --> 00:41:09,927 Catalyst article about the future of law made me realize something I thought they were the VCs were hitting us up because we've had really strong growth and it's very visible on 556 00:41:09,927 --> 00:41:13,458 LinkedIn just by headcount So was like, that's why they're hitting us up. 557 00:41:13,458 --> 00:41:26,992 But after I read that I was like, oh there is a broader investment thesis that what we're doing aligns to and I never really I never realized how smart these funds are in 558 00:41:26,992 --> 00:41:29,062 understanding like 559 00:41:29,929 --> 00:41:33,822 these are some of the smartest people ever go into these spaces. 560 00:41:33,822 --> 00:41:39,398 And VCs, boy, their whole value prop is upside down right now. 561 00:41:39,398 --> 00:41:42,371 So they're trying to figure out how to survive too, right? 562 00:41:42,371 --> 00:41:44,053 Because AI is flipping everything. 563 00:41:44,053 --> 00:41:47,126 You don't need those kinds of big investments anymore for engineering. 564 00:41:47,287 --> 00:41:50,802 So they're nervous. 565 00:41:50,802 --> 00:41:55,323 a lot of money on the sideline that needs to find a home and it's kind of their job to do it. 566 00:41:55,323 --> 00:42:00,344 this was written like I wrote it and I've been in the space 20 years. 567 00:42:00,344 --> 00:42:02,305 I host a podcast on it. 568 00:42:02,305 --> 00:42:03,655 I speak at conferences. 569 00:42:03,655 --> 00:42:11,317 I attend conferences and this VC wrote what I thought was a fantastic outlook for where legal is going. 570 00:42:11,317 --> 00:42:12,968 So anyway, we were... 571 00:42:13,328 --> 00:42:13,862 yeah. 572 00:42:13,862 --> 00:42:14,774 guys send me a link. 573 00:42:14,774 --> 00:42:15,554 really good. 574 00:42:15,554 --> 00:42:16,805 It's really good. 575 00:42:16,945 --> 00:42:26,330 But so how does a of a bootstrapped company, you know, a two person bootstrap company go about competing with these? 576 00:42:26,330 --> 00:42:27,690 I mean, you've told your story. 577 00:42:27,690 --> 00:42:29,671 Is your story repeatable? 578 00:42:29,671 --> 00:42:31,872 is that a playbook people can use? 579 00:42:32,174 --> 00:42:33,734 I mean, yes and no. 580 00:42:33,734 --> 00:42:36,694 here's the other kind of thing that's cool. 581 00:42:36,694 --> 00:42:44,034 Like everybody always thinks that 20 whatever year old, you know, startup people are magic and they are. 582 00:42:44,154 --> 00:42:51,914 But when you're a startup founder in a different part of your career, later in your career, you can kind of do things a little differently too. 583 00:42:51,914 --> 00:42:58,154 Like hopefully you have a little bit of your own money you can invest or you have a little more, you know, ability to kind of do it the way you want. 584 00:42:58,614 --> 00:43:00,800 I would say that, you know, 585 00:43:00,800 --> 00:43:02,151 depending on where you are in your life. 586 00:43:02,151 --> 00:43:06,134 um Because, you know, we did invest in it, right? 587 00:43:06,134 --> 00:43:10,918 We invested time and, you know, it's not like open AI was giving us free credits, you know what I mean? 588 00:43:10,918 --> 00:43:16,453 Like, so there was some significant investment, but, we invested it ourselves, right? 589 00:43:16,453 --> 00:43:26,061 And so since we didn't have to pay for engineering, which is really expensive, and we didn't have to pay for marketing, which is also really expensive, like we saved a ton of 590 00:43:26,061 --> 00:43:26,251 money. 591 00:43:26,251 --> 00:43:30,794 So I say, yes, it's repeatable um for the right 592 00:43:31,288 --> 00:43:32,688 people, if that makes sense. 593 00:43:32,688 --> 00:43:42,341 you kind of, have to have some of your own resources and you have to be tenacious as hell. 594 00:43:42,341 --> 00:43:43,079 You know what I mean? 595 00:43:43,079 --> 00:43:44,942 It's like, it is hard. 596 00:43:45,022 --> 00:43:47,262 It is hard, but it is fun. 597 00:43:47,342 --> 00:43:52,784 and I do, did you, I used to not have gray hair. 598 00:43:53,064 --> 00:43:54,744 So there you go. 599 00:43:54,744 --> 00:44:00,638 But I also think, and this is like a bit esoteric, so forgive me, but I do also think AI, 600 00:44:00,706 --> 00:44:12,029 We talk about this on the show a lot with VCs and stuff like, I think AI is going to also help us think about different ways we fund things because right now we have like a very 601 00:44:12,029 --> 00:44:13,729 broken model, I think. 602 00:44:13,850 --> 00:44:21,672 And this is where state governments, if they're smart, they're going to start to step in and things like that, which, you know, smart government can be like maybe a a big ask. 603 00:44:21,672 --> 00:44:29,814 But, you know, we have, we have, if you're a nonprofit and you want to go the full altruistic route, there's resources for you to build. 604 00:44:29,814 --> 00:44:30,456 Right. 605 00:44:30,456 --> 00:44:33,888 There's grants, there's foundations, there's all kinds of stuff. 606 00:44:33,888 --> 00:44:39,198 If you want to go the full, I'm going to charge as much as I possibly can for my product and make as much money as possible. 607 00:44:39,198 --> 00:44:43,693 So someone wants to buy me and I have an exit, we have a model for that, right? 608 00:44:43,693 --> 00:44:51,728 A model like ours where we're like, I could be charging 30 times more for what we have, but I'm not because I'm trying to do something that's in between. 609 00:44:51,728 --> 00:44:53,779 It's like a social entrepreneurship, whatever. 610 00:44:53,779 --> 00:44:59,394 There's very limited money structures, support, even thinking around. 611 00:44:59,394 --> 00:45:04,358 how to build there and that's sad because that is where there's so much opportunity. 612 00:45:04,358 --> 00:45:15,005 So I think like the challenge and the call I will put out if there's any politicos or like people in any space to think about this, like there's a real opportunity there to rethink 613 00:45:15,005 --> 00:45:21,570 how we even fund ah sort of disruptive technologies right now. 614 00:45:21,692 --> 00:45:23,183 Yeah, no, that's a great point. 615 00:45:23,183 --> 00:45:33,559 mean, you know, uh VCs, PE, growth equity, all of these funding models have to generate return for their investment. 616 00:45:33,559 --> 00:45:41,234 And if you're leaving money on the table, which you are intentionally, it's, it's, I don't know that that's the right fit for them. 617 00:45:41,494 --> 00:45:44,035 No, they think they don't understand. 618 00:45:44,035 --> 00:45:47,577 It's truly bizarre to them. 619 00:45:49,198 --> 00:45:57,411 But they're going to have to adapt because the model for what people are building is going to change and they're going to be left out because people aren't going to take their money 620 00:45:57,411 --> 00:45:59,353 and then jack their prices off. 621 00:45:59,353 --> 00:46:02,645 And the younger generations want to make meaningful change. 622 00:46:02,645 --> 00:46:04,206 They don't want to just be rich. 623 00:46:04,206 --> 00:46:05,146 Some do. 624 00:46:05,192 --> 00:46:05,843 it's true. 625 00:46:05,843 --> 00:46:06,143 Yeah. 626 00:46:06,143 --> 00:46:10,299 mean, rich can be, you know, a byproduct of just doing good things. 627 00:46:10,299 --> 00:46:13,063 Um, that's the hope, right? 628 00:46:13,063 --> 00:46:13,762 And 629 00:46:13,762 --> 00:46:23,994 Yeah, they call it in Massachusetts, our former Secretary of Economic Development, um Yvonne Howe used to call it, do well by doing good. 630 00:46:24,295 --> 00:46:25,535 I love that. 631 00:46:25,576 --> 00:46:27,149 There's no reason you can't have both. 632 00:46:27,149 --> 00:46:28,000 It makes sense. 633 00:46:28,000 --> 00:46:34,752 mean, you know, there are, could go take some funding and probably go grow a heck of a lot faster and probably end up at a bigger payday. 634 00:46:34,752 --> 00:46:35,263 But you know what? 635 00:46:35,263 --> 00:46:36,453 I love what I do. 636 00:46:36,453 --> 00:46:37,901 I'm growing incrementally. 637 00:46:37,901 --> 00:46:40,425 I mean, we're having over a hundred percent year over year growth. 638 00:46:40,425 --> 00:46:43,736 It's not like it's slow, but I'm enjoying it. 639 00:46:43,736 --> 00:46:53,724 I like having some VC breathing down my neck telling me I got to push harder or I have to, you know, fire people that aren't meeting these criteria. 640 00:46:54,114 --> 00:46:55,576 Or you get bumped out, right? 641 00:46:55,576 --> 00:46:56,892 They're like, oh, nevermind. 642 00:46:56,892 --> 00:46:57,806 Thanks for building this. 643 00:46:57,806 --> 00:46:58,278 Bye bye. 644 00:46:58,278 --> 00:46:59,299 Right, exactly. 645 00:46:59,299 --> 00:47:03,371 And that's just not, I'm at a stage in my life where I don't need to do that. 646 00:47:03,371 --> 00:47:05,752 And I'm just having a lot of fun. 647 00:47:05,752 --> 00:47:07,373 My reputation matters to me. 648 00:47:07,373 --> 00:47:13,163 I want to deliver great work to people and hold my head high when I walk around a legal tech conference, you know. 649 00:47:13,163 --> 00:47:15,386 Maybe we need our own organization, Ted. 650 00:47:15,386 --> 00:47:19,730 Maybe like these stubborn GenX boot strappers. 651 00:47:19,730 --> 00:47:23,496 We need our own little conference. 652 00:47:23,496 --> 00:47:34,894 You know what I have thought about honestly, in the past, some sort of like, um, model with which vendors could kind of organize and collaborate. 653 00:47:34,894 --> 00:47:37,456 And I haven't figured out how to do that yet. 654 00:47:37,456 --> 00:47:41,969 And I'm so busy with my day job, but, um, I started a franchisee association. 655 00:47:41,969 --> 00:47:43,970 My wife and I own five gyms here in St. 656 00:47:43,970 --> 00:47:51,295 Louis and, that brand needed some help on the franchisee side that we weren't getting from HQ. 657 00:47:51,295 --> 00:47:52,606 They're great, but. 658 00:47:52,606 --> 00:47:54,917 They were growing so fast, they weren't giving support. 659 00:47:54,917 --> 00:47:59,036 So I started a nonprofit and it was wildly successful. 660 00:47:59,036 --> 00:48:00,430 I handed over the keys. 661 00:48:00,430 --> 00:48:03,502 It's still doing great, but man, I got so much. 662 00:48:03,502 --> 00:48:05,222 created mentoring programs. 663 00:48:05,222 --> 00:48:08,743 We did a summit where we brought everybody together. 664 00:48:08,743 --> 00:48:12,806 uh We brought in speakers and it was great. 665 00:48:12,806 --> 00:48:13,867 That's not a bad idea. 666 00:48:13,867 --> 00:48:15,882 Maybe you and I should connect at Ilta. 667 00:48:15,882 --> 00:48:16,722 talk, yeah. 668 00:48:16,722 --> 00:48:26,305 And then we should encourage, from my branding perspective, we should encourage the big players to help fund this because we're going after markets they don't want anyway, or at 669 00:48:26,305 --> 00:48:27,186 least I am. 670 00:48:27,186 --> 00:48:35,848 So it can be like, fine, help the innovation economy, but don't worry, it's not people who want your customers and then they can look like the good guys in the room who are helping 671 00:48:35,848 --> 00:48:38,139 uh increase access to the law. 672 00:48:38,139 --> 00:48:39,688 There you go, boom, done. 673 00:48:39,688 --> 00:48:40,219 I like it. 674 00:48:40,219 --> 00:48:43,418 They won't they won't like me though because I am taking their market share. 675 00:48:43,418 --> 00:48:44,163 competing with them. 676 00:48:44,163 --> 00:48:45,724 Okay, but we'll keep you. 677 00:48:45,724 --> 00:48:46,864 You can be a silent person. 678 00:48:46,864 --> 00:48:48,608 Exactly, exactly. 679 00:48:48,608 --> 00:48:50,792 Well, this has been a great conversation. 680 00:48:50,792 --> 00:48:58,948 um Before we wrap up, just tell people how they can find more out about what you do, your podcasts, stuff like that. 681 00:48:59,278 --> 00:49:00,318 Yeah, great. 682 00:49:00,318 --> 00:49:04,378 So first of all, if you happen to be at Ilticon, come by the Startup Hub. 683 00:49:04,378 --> 00:49:07,338 Booth 123 will be hanging out and would love to meet you. 684 00:49:07,338 --> 00:49:09,098 You can always check out our website. 685 00:49:09,098 --> 00:49:14,618 It's describe with a Y because, you know, startups have to have weirdly spelled names. 686 00:49:14,878 --> 00:49:17,098 So describe.com with a Y. 687 00:49:17,098 --> 00:49:21,938 We're most active on LinkedIn, which is kind of like where the Legal Tech people hang out. 688 00:49:21,938 --> 00:49:23,698 So find me on there. 689 00:49:23,698 --> 00:49:25,398 Happy to connect. 690 00:49:25,738 --> 00:49:27,578 Ping us, stop by. 691 00:49:27,804 --> 00:49:32,132 the booth and yeah, just love to love to talk to people in the community. 692 00:49:32,132 --> 00:49:33,402 It's the best part of the job. 693 00:49:33,402 --> 00:49:33,882 Awesome. 694 00:49:33,882 --> 00:49:36,664 And InfoDash will be in booth 308 as well. 695 00:49:36,664 --> 00:49:39,836 So stop by there after you stop by describes. 696 00:49:39,836 --> 00:49:42,417 um Well, this has been a great conversation. 697 00:49:42,417 --> 00:49:44,408 I look forward to seeing you next week. 698 00:49:44,408 --> 00:49:46,799 And let's keep the conversation going. 699 00:49:47,042 --> 00:49:48,500 Great, thanks Ted, this was really fun. 700 00:49:48,500 --> 00:49:50,478 I'm so happy to have joined you, thank you. 701 00:49:50,478 --> 00:49:50,891 Awesome. 702 00:49:50,891 --> 00:49:51,877 You're very welcome. 703 00:49:51,877 --> 00:49:52,869 Take care. 704 00:49:53,420 --> 00:49:54,332 Bye bye. 00:00:03,846 Kara, how are you this morning? 2 00:00:04,084 --> 00:00:04,738 I'm good. 3 00:00:04,738 --> 00:00:05,817 How are doing Ted? 4 00:00:05,817 --> 00:00:08,879 I'm doing great, doing great. 5 00:00:08,879 --> 00:00:20,828 You and I were, I saw a thread on LinkedIn about some open source data and you had made a comment in there that opened my eyes to some things that I didn't know. 6 00:00:20,949 --> 00:00:32,787 So you and I jumped on a call, you educated me a little bit and um I think we have a really interesting conversation to be had because I can tell, I see that post. 7 00:00:33,437 --> 00:00:42,843 a million times and I think a lot of people don't understand all the details and nuance behind it and yeah, it'll be good to kind of get some clarity around that. 8 00:00:42,843 --> 00:00:46,695 um But before we do, let's get you introduced. 9 00:00:46,695 --> 00:00:50,948 So you and I were actually on a podcast together. 10 00:00:50,948 --> 00:00:53,189 Was that a year ago or two years ago? 11 00:00:53,486 --> 00:00:54,786 Yeah, let's see. 12 00:00:54,786 --> 00:00:59,286 We, we launched like two years ago, so it has to have been within the past two year window. 13 00:00:59,286 --> 00:01:00,786 I just can't remember when. 14 00:01:00,786 --> 00:01:01,521 Yeah. 15 00:01:01,521 --> 00:01:09,838 and I think Horace and Max from Lagora and um maybe the guy from LegalOn. 16 00:01:09,838 --> 00:01:16,404 um But anyway, so you are the co-founder of Describe AI. 17 00:01:16,404 --> 00:01:19,966 You have a A to J focus. 18 00:01:19,966 --> 00:01:23,309 um You actually host a podcast yourself. 19 00:01:23,309 --> 00:01:28,133 Why don't you kind of in the gaps there and tell us a little bit about 20 00:01:28,137 --> 00:01:30,468 who you are, what you do, and where you do it. 21 00:01:31,160 --> 00:01:31,500 Sure. 22 00:01:31,500 --> 00:01:31,940 Yeah. 23 00:01:31,940 --> 00:01:32,581 Thanks so much. 24 00:01:32,581 --> 00:01:34,211 It's really exciting to be on your show. 25 00:01:34,211 --> 00:01:35,122 That was a fun one. 26 00:01:35,122 --> 00:01:35,622 remember that. 27 00:01:35,622 --> 00:01:37,232 Horace always does a great show too. 28 00:01:37,232 --> 00:01:38,733 So that's a good one. 29 00:01:38,733 --> 00:01:39,513 Yeah, he does. 30 00:01:39,513 --> 00:01:42,365 um I'm, Cara Peterson. 31 00:01:42,365 --> 00:01:53,499 So I'm the co-founder of Describe AI and we are a two-year-old legal research company that em we like to think of ourselves sort of as the mavericks of legal research. 32 00:01:53,499 --> 00:01:58,741 So we've been called, some have called us the Robin Hood of legal research, which is a fun one too. 33 00:01:58,741 --> 00:02:00,610 But our, um 34 00:02:00,610 --> 00:02:11,421 whole goal is to really try to create tools that help um change the way people can access what should be, at least in theory, somewhat public information. 35 00:02:11,421 --> 00:02:14,884 So that's why I think that post was so interesting to me. 36 00:02:14,884 --> 00:02:25,214 And so as I've gotten really interested in AI over the past couple of years and sort of all the things that it can do to change so many different parts of our society. 37 00:02:25,230 --> 00:02:27,281 That's where the show came in that I started. 38 00:02:27,281 --> 00:02:29,132 called Building AI Boston. 39 00:02:29,132 --> 00:02:34,613 And that's all about how AI is being used by real people to do really interesting things. 40 00:02:34,613 --> 00:02:39,015 So it's beyond legal tech, but legal tech does pop up here and there. 41 00:02:39,015 --> 00:02:40,555 So that's me. 42 00:02:40,676 --> 00:02:41,836 Those are my two hats. 43 00:02:41,836 --> 00:02:46,257 And then my third hat is I have a real job that pays me, but we'll talk about that tomorrow. 44 00:02:46,623 --> 00:02:47,324 Okay. 45 00:02:47,324 --> 00:02:48,384 Good stuff. 46 00:02:48,384 --> 00:02:55,744 Well, let's, yeah, let's talk about this, this open source data movement, legal data movement and you know, what's reality? 47 00:02:55,744 --> 00:02:56,944 What's, what's hype? 48 00:02:56,944 --> 00:03:12,242 Um, I think it was kind of an interesting headline grabbing, um, post that talked about, you know, 99 % of case law was being open sourced and 49 00:03:12,242 --> 00:03:21,097 You you had chimed in with some interesting um comments just around kind of what that really means. 50 00:03:21,097 --> 00:03:26,560 It sounds like some of this data has actually been around for a long time, but might be somewhat dated. 51 00:03:26,560 --> 00:03:32,203 Like, of separate the fact and fiction around these recent announcements. 52 00:03:33,582 --> 00:03:34,322 Right, sure. 53 00:03:34,322 --> 00:03:39,042 So this was one of those things where I saw it come through my LinkedIn feed. 54 00:03:39,042 --> 00:03:43,502 sometimes you have those moments where you're like, should I jump on this one? 55 00:03:43,502 --> 00:03:44,202 Should I not? 56 00:03:44,202 --> 00:03:45,782 And so I kind of sat on it for a little bit. 57 00:03:45,782 --> 00:03:47,282 And then I decided, you know what? 58 00:03:47,282 --> 00:03:50,662 Yeah, I'm going to put in my two cents here. 59 00:03:50,742 --> 00:03:55,862 So the gist of it was when you think about case law. 60 00:03:55,862 --> 00:03:57,122 So that's what Describe has. 61 00:03:57,122 --> 00:03:59,982 have all kinds of case law right from across the country. 62 00:04:00,002 --> 00:04:02,542 And that is public information. 63 00:04:02,542 --> 00:04:02,982 Right? 64 00:04:02,982 --> 00:04:08,782 mean, so in theory, you should just be able to get whatever you need and get your access to that easily and so on and so forth. 65 00:04:08,782 --> 00:04:10,722 But we all know that's not the case. 66 00:04:10,922 --> 00:04:18,182 what we've done as a company is like find ways to get that case law and do things to it, which makes it more usable. 67 00:04:18,182 --> 00:04:22,922 But this post was really interesting to me because there's a few threads. 68 00:04:22,922 --> 00:04:29,774 One, and that I'm super in favor of is this open source kind of like making materials. 69 00:04:29,774 --> 00:04:35,254 available for people, although we have followed a slightly different path that describes it, which we can talk about later. 70 00:04:35,254 --> 00:04:41,114 And so what should be more available to people than our own laws, like, obviously. 71 00:04:41,134 --> 00:04:50,954 So this post was interesting because it was sort of presenting in some way that access to this case law unhugging face, which is great that they're doing this, that they're posting 72 00:04:50,954 --> 00:04:53,714 this, was somehow new and different. 73 00:04:53,914 --> 00:04:58,122 But anyone who's been around in this space for a while knows that this 74 00:04:58,122 --> 00:04:59,884 is not actually a new effort. 75 00:04:59,884 --> 00:05:04,788 And so I just wanted to jump in there and sort of talk about what's actually happening in that space. 76 00:05:04,788 --> 00:05:11,324 And then there was a second part about it that this was the reason I really jumped on it was that, oh, the case was there. 77 00:05:11,324 --> 00:05:21,994 So anyone can just throw an AI wrapper on it and make some tools that can compete with all the established legal research tools, which that's the part where I'm like, no, no, no, we 78 00:05:21,994 --> 00:05:24,206 need to talk about this. 79 00:05:24,220 --> 00:05:33,433 Yeah, I mean, there are multi-billion dollar companies that have built themselves on legal research, TR, Lexis, Bloomberg, others. 80 00:05:33,534 --> 00:05:37,459 And yeah, if it were just that simple, they'd be out of business. 81 00:05:37,459 --> 00:05:38,581 why is it? 82 00:05:38,581 --> 00:05:40,663 Tell us why it's not that simple. 83 00:05:41,314 --> 00:05:50,770 Right, so you can, anyone could get access, you know, and for first I should just say as a disclaimer, I am the sort of marketing business development side of our company. 84 00:05:50,770 --> 00:05:56,444 We have obviously another side that's the tech side, my co-founder Richard DeBona. 85 00:05:56,444 --> 00:06:00,067 So when I talk about this, I'm talking about it from more like the business perspective. 86 00:06:00,067 --> 00:06:04,390 He has much more, you know, deep thinking about how the tech actually works. 87 00:06:04,390 --> 00:06:08,973 But the point is, is just because it's there doesn't mean you can make it useful, right? 88 00:06:08,973 --> 00:06:10,786 You still need to be able to 89 00:06:10,786 --> 00:06:20,281 build tools with AI and with other types of technologies to mine the information that's useful for the user of that data. 90 00:06:20,281 --> 00:06:21,632 So it's very easy. 91 00:06:21,632 --> 00:06:32,878 as we've seen, people who are going directly into things like ChachiBT or whatnot to do legal research or legal um work are coming across. 92 00:06:32,878 --> 00:06:38,198 very significant problems that that data set will have for them, including hallucinations and things like that. 93 00:06:38,198 --> 00:06:41,258 So it was vastly oversimplifying. 94 00:06:41,258 --> 00:06:42,818 And again, it's just someone's post. 95 00:06:42,818 --> 00:06:52,638 It's not like, you know, they were writing a white paper or something, but just to vastly oversimplify that people can grab that data, take some kind of chat GPT wrapper, throw it 96 00:06:52,638 --> 00:07:02,298 on there, and you're going to create a tool that's helpful for people and furthering sort of access to the law or access to justice or the democratization of this information was 97 00:07:02,420 --> 00:07:08,797 so misleading and so many people were jumping on that post and saying, wow, this is game changing. 98 00:07:08,797 --> 00:07:09,909 It's gonna change everything. 99 00:07:09,909 --> 00:07:12,541 It just rubbed me the wrong way. 100 00:07:12,942 --> 00:07:16,754 Cause that it'll cause more harm than good if people think that's the result. 101 00:07:16,754 --> 00:07:19,466 Yeah, you know, I see it all the time. 102 00:07:19,466 --> 00:07:21,964 In fact, there's a guy I follow. 103 00:07:21,964 --> 00:07:28,091 I won't say his name, but he's a, he has really great content around AI use cases. 104 00:07:28,091 --> 00:07:35,275 And yesterday he posted that he just replaced his lawyer with this prompt. 105 00:07:35,275 --> 00:07:40,998 And you know, it looks, it's a, it's a great prompt, but there's, it's just not that simple. 106 00:07:40,998 --> 00:07:44,100 And I am definitely in the camp of. 107 00:07:44,167 --> 00:07:50,520 AI today, the general models can drastically reduce the amount of legal spend. 108 00:07:50,520 --> 00:07:54,042 Um, but it does not eliminate the need for lawyers. 109 00:07:54,042 --> 00:08:05,808 Like I gave you some examples, like we have, um, we have a four nine a program here, which is like a, a way that we incent, certain people on the team with like shadow equity in the 110 00:08:05,808 --> 00:08:06,748 company. 111 00:08:06,949 --> 00:08:13,522 And, we start, we started this program before AI existed. 112 00:08:13,522 --> 00:08:14,068 Well, 113 00:08:14,068 --> 00:08:22,187 before November of 2022 when, you know, chat GPT-35 was released, before it was easily accessible. 114 00:08:22,187 --> 00:08:29,488 So I just for the hell of it decided to upload our docs into chat GPT. 115 00:08:29,488 --> 00:08:31,068 Actually, I used Grok for that one. 116 00:08:31,068 --> 00:08:37,828 I've been playing around with Grok and asked for, are there any irregularities or risks associated with how we've implemented this program? 117 00:08:37,828 --> 00:08:42,528 And then I said, give me a risk ranking. 118 00:08:42,704 --> 00:08:46,948 and a probability that one of these risks could potentially materialize. 119 00:08:46,948 --> 00:08:48,730 And it did a fantastic job. 120 00:08:48,730 --> 00:08:52,353 And then I took that to our lawyers, and then we had a conversation about it. 121 00:08:52,353 --> 00:09:00,059 um So it doesn't eliminate the need for lawyers, but it can today, the general model is not a legal specific tool. 122 00:09:01,401 --> 00:09:05,605 There are some really valuable use cases, especially for small businesses like ours. 123 00:09:05,605 --> 00:09:09,330 We're like 43 people, and um we don't have 124 00:09:09,330 --> 00:09:10,891 big legal budgets. 125 00:09:10,891 --> 00:09:16,163 it's a good way for us to just do sanity checks, um especially on lower risk stuff. 126 00:09:16,163 --> 00:09:18,503 Like I don't even read NDAs anymore. 127 00:09:18,564 --> 00:09:26,157 You know, I will, if they, if they send me an NDA, I have a, I have a custom GPT that I've trained and say, Hey, what's the Delta? 128 00:09:26,157 --> 00:09:27,888 Are there any, is this one sided? 129 00:09:27,888 --> 00:09:30,298 Have a little prompt that I use takes me there. 130 00:09:30,298 --> 00:09:31,609 They're low risk. 131 00:09:31,609 --> 00:09:37,391 So, um, for high risk stuff, obviously lawyers still need to be involved in the real nuanced. 132 00:09:37,391 --> 00:09:39,465 Um, but 133 00:09:39,465 --> 00:09:49,693 What, you know, your comment about, yeah, you can't just throw chachi BT point chachi BT at these big expansive data sources for a number of reasons. 134 00:09:49,693 --> 00:10:04,125 mean, one, the context window issue, like even I think Gemini that I think is now at a million tokens, it gets all sorts of detail gets lost in the middle when you upload a ton 135 00:10:04,125 --> 00:10:08,488 of content and try to do retrieval or 136 00:10:08,698 --> 00:10:12,315 summarize it misses things today's tech does. 137 00:10:12,315 --> 00:10:16,663 What are some other challenges with just pointing it at a big data source? 138 00:10:16,663 --> 00:10:21,972 I don't mean from a technical perspective, but you know, just kind of data wise, what are the issues? 139 00:10:22,156 --> 00:10:28,139 Well, and I think your point about the nuance is really important and also your point about risk, right? 140 00:10:28,139 --> 00:10:37,034 So if you think about when you're in a situation, like think about it from the consumer of legal information or legal services point of view, right? 141 00:10:37,034 --> 00:10:38,195 So the client point of view. 142 00:10:38,195 --> 00:10:47,150 So most likely if you're engaging in some kind of legal dispute or legal situation, you have a pretty serious thing that you're trying to work through, right? 143 00:10:47,150 --> 00:10:51,682 So for, when you talk about the risk profile of something being wrong, 144 00:10:51,828 --> 00:11:03,351 it's much scarier how it could affect people's lives in a legal sphere or a medical sphere or something like that versus apartment hunting or planning a trip or things like that. 145 00:11:03,351 --> 00:11:09,343 And now this is all coming from someone who's very AI positive and very much a pro AI. 146 00:11:09,343 --> 00:11:11,250 I obviously I have show about it. 147 00:11:11,250 --> 00:11:12,164 I have a company about it. 148 00:11:12,164 --> 00:11:19,346 So I'm super, super uh excited about the potential the same way you are about how it can help humans become better at what they're doing. 149 00:11:19,346 --> 00:11:20,642 But I do think 150 00:11:20,642 --> 00:11:32,893 the biggest risk I see about this idea of just pointing at all this data, having people who frankly don't have the depth of knowledge either in the legal sphere and the tech 151 00:11:32,893 --> 00:11:35,555 sphere to understand what's coming back. 152 00:11:35,555 --> 00:11:36,115 Is it good? 153 00:11:36,115 --> 00:11:36,486 it bad? 154 00:11:36,486 --> 00:11:37,577 I mean, this is really hard. 155 00:11:37,577 --> 00:11:38,788 Benchmarking is really hard. 156 00:11:38,788 --> 00:11:39,959 We can talk about that too. 157 00:11:39,959 --> 00:11:44,076 em Because we could end up as a community. 158 00:11:44,076 --> 00:11:49,099 destroying any possibility we have of having these two will be helpful before they even get out of the gate. 159 00:11:49,099 --> 00:12:00,324 And so I'm probably not surprising anybody listening to this call that the judiciary um is not necessarily or the people involved in the courts and things of that nature aren't 160 00:12:00,324 --> 00:12:03,876 necessarily the most technically advanced people on earth, know, right? 161 00:12:04,157 --> 00:12:06,238 They just are and it's okay. 162 00:12:06,238 --> 00:12:09,140 And um that's not necessarily their job. 163 00:12:09,140 --> 00:12:14,122 But if you can see, and we saw it with hallucinations, if we create 164 00:12:14,270 --> 00:12:26,319 noise and we create situations where people are causing themselves, like we said, or the system more harm than good, we could end up getting shut down, you know, regulated to a 165 00:12:26,319 --> 00:12:31,802 point where we're actually hurting the long-term goals of what AI could do. 166 00:12:32,050 --> 00:12:42,870 and this, now I'm going to sound a little bit, a little bit uh soapboxy here, but some of this can come to the point of everyone's trying to make their dollar. 167 00:12:43,060 --> 00:12:43,612 on these tools. 168 00:12:43,612 --> 00:12:49,596 And of course I am too, so I'm not criticizing, but you know, it's a very different space when you're in the legal space. 169 00:12:49,596 --> 00:12:50,117 Yeah. 170 00:12:50,117 --> 00:12:52,039 Well, you mentioned benchmarking. 171 00:12:52,039 --> 00:12:55,143 What are your thoughts around that? 172 00:12:55,842 --> 00:12:57,583 Yeah, so benchmarking. 173 00:12:57,583 --> 00:13:00,744 So some of this is I come at it like I'm not an attorney. 174 00:13:00,744 --> 00:13:03,095 uh I don't have a legal background. 175 00:13:03,095 --> 00:13:07,607 have, like I said, a marketing, public health, of like social justice background, right? 176 00:13:07,607 --> 00:13:11,109 um But what do I know about these things, you know? 177 00:13:11,109 --> 00:13:22,828 And so when you think about legal tech as a field, as an ecosystem, you know, we haven't done a very good job of helping people assess what tools are good. 178 00:13:22,828 --> 00:13:29,324 what tools aren't good, what tools might work for them, which tools have the better housekeeping, know, seal approval. 179 00:13:29,384 --> 00:13:37,992 And I know there's a lot of discussion going on around this, particularly in the academic circles and with the legal librarians who are the people who probably will solve this for 180 00:13:37,992 --> 00:13:40,074 us eventually, which is great. 181 00:13:40,535 --> 00:13:45,329 But we're not giving consumers a very easy way to understand what's good and what's not. 182 00:13:45,329 --> 00:13:46,911 And again, I'm part of this. 183 00:13:46,911 --> 00:13:48,482 I'm not, you know, 184 00:13:48,482 --> 00:13:52,964 blaming others and saying we're perfect, but we tend to say, my product is good, trust me. 185 00:13:52,964 --> 00:13:57,066 And I'm patting my back for the people who are just watching, listening and not watching. 186 00:13:57,066 --> 00:14:06,531 em And that's not going to be enough for something like this because again, the consequences are too dire for people getting incorrect information. 187 00:14:06,531 --> 00:14:12,334 that's where the whole, excuse me, the whole human in the loop thing becomes very, very, very important. 188 00:14:12,348 --> 00:14:15,382 Yeah, and you know, I have seen some initiatives. 189 00:14:15,382 --> 00:14:20,353 It's been a while that probably Gosh, maybe close to a year ago. 190 00:14:20,353 --> 00:14:24,448 I heard about a uh consortium of 191 00:14:24,624 --> 00:14:27,145 sorts that had kind of gotten together. 192 00:14:27,145 --> 00:14:31,547 Harvey was on that list as participants, which I thought was interesting. 193 00:14:31,547 --> 00:14:38,810 I'm not sure how much vendors should play a role, maybe an advisory role, but I don't, you know, it's kind of like the Fox garden, the hen house. 194 00:14:38,810 --> 00:14:43,412 If the Pete, you creating your own, you grading your own tests. 195 00:14:43,412 --> 00:14:54,546 Um, we've seen gaming in, I mean, meta got slapped around pretty hard, not long ago with llama four and the, um, 196 00:14:54,546 --> 00:15:06,030 model that was released had material differences in benchmarking scores than what they presented during those benchmarking tests. 197 00:15:06,030 --> 00:15:14,800 yeah, think vendors should play a role, you know, feels like, I don't know, somebody else should be leading that effort with us supporting them. 198 00:15:15,327 --> 00:15:15,717 Agree. 199 00:15:15,717 --> 00:15:17,088 And it needs to be independent. 200 00:15:17,088 --> 00:15:22,211 And this is why I'm really in favor of it coming out of educational institutions. 201 00:15:22,211 --> 00:15:25,012 uh I worked in higher education for a long time. 202 00:15:25,012 --> 00:15:31,096 So I know that that's probably the best that we have for an independent lens. 203 00:15:31,096 --> 00:15:36,138 Excuse me, because um these firms that are marketing firms for legal tech are great. 204 00:15:36,139 --> 00:15:42,094 And, of course, they're going to do thorough, you know, sort of 205 00:15:42,094 --> 00:15:52,334 looking at these tools, but if it's a client or if it's a tool that is using their services, it's still hard for people to feel that it's completely independent. 206 00:15:52,334 --> 00:15:57,354 And I don't think in the current environment, the government is going to be doing anything about this. 207 00:15:57,374 --> 00:16:01,594 We couldn't really ask OpenAI or the other models to test it either. 208 00:16:01,594 --> 00:16:02,794 So it's a tough one. 209 00:16:02,794 --> 00:16:03,674 I don't know. 210 00:16:03,674 --> 00:16:09,834 And it's not regulated the way medical information or things like that is in some ways. 211 00:16:10,794 --> 00:16:22,622 I would say if there's anyone out there uh who wants to do this, I think you have a big wide open field and I think you should make the legal tech companies pay you for it and 212 00:16:22,622 --> 00:16:23,388 support it. 213 00:16:23,388 --> 00:16:24,989 Yeah, I agree. 214 00:16:24,989 --> 00:16:28,991 Now back to the kind of legal data movement. 215 00:16:28,991 --> 00:16:43,329 um You had, when you and I talked last, you had shared some interesting information on just kind of the history of the legal data liberation efforts, you know, in the Harvard 216 00:16:43,329 --> 00:16:46,561 case law project and the uh free law project. 217 00:16:46,561 --> 00:16:53,256 give, give our listeners a little bit of a perspective on where we've been and kind of 218 00:16:53,256 --> 00:16:54,607 where we are now. 219 00:16:55,438 --> 00:16:56,438 Right. 220 00:16:56,458 --> 00:17:05,098 So, and I'm sure there's things I don't know about, so I'll tell you the things I know, and then folks can put chime in in the comments about things they know too. 221 00:17:05,178 --> 00:17:10,978 So the first place that we came across is we were looking for case law ourselves a couple of years ago. 222 00:17:10,978 --> 00:17:13,738 The first place we found, you know, good access. 223 00:17:13,738 --> 00:17:22,478 And then there's also the idea of access to users to research and the access to people who want to use that technology to create a product, right? 224 00:17:22,478 --> 00:17:25,658 Or that, excuse me, that information to create a product, which are not the same. 225 00:17:26,638 --> 00:17:34,938 So the case law access project, which was out of the Harvard Law School's library, was a very interesting project that we came across. 226 00:17:34,938 --> 00:17:36,958 And they had all the case law. 227 00:17:36,958 --> 00:17:38,498 They have a wonderful story. 228 00:17:38,498 --> 00:17:42,118 Adam Ziegler could come on and talk about it if you want, I'm sure. 229 00:17:42,118 --> 00:17:43,658 Although you probably have to ask him. 230 00:17:43,658 --> 00:17:44,918 I'm not his rep. 231 00:17:45,038 --> 00:17:49,438 Where they went into the library and they quite literally scanned all their books. 232 00:17:49,438 --> 00:17:55,466 And there's just a fascinating story about how they had to break the bindings and the librarians were like, ah. 233 00:17:55,466 --> 00:17:56,306 some of these old books. 234 00:17:56,306 --> 00:18:06,651 anyway, so they scanned everything they had and they collaborated with a legal tech company that I'm forgetting the name right now, but um they uh worked with them. 235 00:18:06,651 --> 00:18:09,793 And then I think that company was sold to one of the big ones. 236 00:18:09,793 --> 00:18:13,934 I think it was Lexis, but may want to fact check me on that. 237 00:18:13,934 --> 00:18:21,318 So their data we noticed stopped around 2017 because that's when the project ended. 238 00:18:21,318 --> 00:18:21,954 So 239 00:18:21,954 --> 00:18:29,130 we had to look for another resource, but that was kind of like the original free the law group from what I've been able to see. 240 00:18:29,130 --> 00:18:30,701 And they're still doing a lot of really cool stuff. 241 00:18:30,701 --> 00:18:33,223 think they're ramping up again. 242 00:18:33,684 --> 00:18:44,613 So then we came across a uh group out in Ottawa, California that is powering a ton of innovation in this ecosystem and should be getting a lot of credit. 243 00:18:44,613 --> 00:18:51,052 And that was one of the other reasons I jumped on that post is because I'm like, hey, free law has been doing this for years. 244 00:18:51,052 --> 00:19:01,908 So the free lab project is, I think they've been around about 10 years and their sole purpose is to make sure that um things like case law and other things are actually 245 00:19:01,908 --> 00:19:03,919 accessible by regular people. 246 00:19:03,919 --> 00:19:10,463 And then they also have, you can create a commercial agreement with them where you ingest their data, which is how we get our data. 247 00:19:10,463 --> 00:19:11,304 So it's great. 248 00:19:11,304 --> 00:19:13,015 And that's a commercial license. 249 00:19:13,015 --> 00:19:14,235 So they're doing that. 250 00:19:14,235 --> 00:19:19,018 um And then a very interesting space that's new and 251 00:19:19,520 --> 00:19:26,913 I think there's a lot of cool things happening here, including at Describe, has to do with sort of the other parts of the law. 252 00:19:26,913 --> 00:19:29,274 Case law is one part of the law. 253 00:19:29,394 --> 00:19:34,766 But a lot of people think of statutes, regulations, and all that other stuff as the real law. 254 00:19:34,766 --> 00:19:39,282 So happy to talk about that, because that's a big missing piece of the puzzle right now. 255 00:19:39,282 --> 00:19:42,668 Yeah, well, let's uh share your thoughts on that. 256 00:19:43,374 --> 00:19:54,914 Yeah, so again, coming from a non-lawyer, so forgive me if I'm not explaining this the way a professor would in law school, but certainly case law is part of what lawyers, attorneys 257 00:19:54,914 --> 00:19:58,534 have to look at as they're building a case or writing a brief or doing things like that. 258 00:19:58,534 --> 00:20:05,254 But of course, much of the law is done with just the law of the land, which statutes, regulations, things of that nature. 259 00:20:05,254 --> 00:20:08,914 And it's really, really hard to get. 260 00:20:09,014 --> 00:20:13,100 It's almost impossible to get, and that's weird. 261 00:20:13,100 --> 00:20:15,802 right, when you think about it, because it's all public information. 262 00:20:15,802 --> 00:20:24,258 And this also, I think, links back to the judiciary in many states, state governments, and things like that don't necessarily have very sophisticated technology. 263 00:20:24,258 --> 00:20:27,320 They can't, you know, it's not something they've invested in. 264 00:20:27,320 --> 00:20:31,103 There are sort of workarounds that other companies have provided to them to make it easier for them. 265 00:20:31,103 --> 00:20:33,044 And then that data is sort of blocked away. 266 00:20:33,044 --> 00:20:40,649 m So uh some companies or some places have started to look at pulling that data directly. 267 00:20:40,649 --> 00:20:42,110 And that is 268 00:20:42,110 --> 00:20:42,600 what we're doing. 269 00:20:42,600 --> 00:20:49,672 So we had looked in because we really need to add those resources to our database for it to be as broad as possible. 270 00:20:49,672 --> 00:20:55,374 em And we started to look at where we could get that data without having to go get it ourselves. 271 00:20:55,374 --> 00:21:05,167 And I think we were quoted by one group who shall remain anonymous, $100,000 just for some small piece of this data. 272 00:21:05,167 --> 00:21:06,717 And so we thought this is absurd. 273 00:21:06,717 --> 00:21:09,476 You know, so 274 00:21:09,656 --> 00:21:10,726 We're getting it ourselves. 275 00:21:10,726 --> 00:21:18,528 So we're going to have every single piece of, tell you the list because I want to make sure I get this right. 276 00:21:18,528 --> 00:21:25,590 Statutes, regulations, state constitutions, court rules, session laws, and attorney general opinions from all 50 states. 277 00:21:25,669 --> 00:21:28,051 And it will be part of our database. 278 00:21:28,051 --> 00:21:30,182 We will be demoing this at Ilticon. 279 00:21:30,182 --> 00:21:31,532 So come by and see it. 280 00:21:31,532 --> 00:21:37,294 But we think we'll have the most thorough corpus of anyone, especially at the prices we charge. 281 00:21:37,294 --> 00:21:39,233 And everything will be fully searchable. 282 00:21:39,233 --> 00:21:40,283 by natural. 283 00:21:40,584 --> 00:21:41,034 Wow. 284 00:21:41,034 --> 00:21:42,675 Yeah, that's big news. 285 00:21:42,675 --> 00:21:44,568 Yeah, that's big news. 286 00:21:44,568 --> 00:21:54,198 we are em recording on Monday the 4th, but this episode will be released on Wednesday the 6th, which is going to be in time for Ilticon so folks can come by. 287 00:21:54,198 --> 00:21:55,719 Are you guys exhibiting? 288 00:21:56,155 --> 00:21:58,476 Yeah, we're in the startup hub, which is cool. 289 00:21:58,476 --> 00:22:00,597 haven't been to Ilticon before. 290 00:22:00,597 --> 00:22:05,460 The only conference we've done before is Tech Show, which was so much fun. 291 00:22:05,460 --> 00:22:06,300 my gosh. 292 00:22:06,300 --> 00:22:09,412 We love that one with Bob Ambrosio and the Startup Alley and stuff. 293 00:22:09,412 --> 00:22:11,833 So anyone out there who's got a startup apply for that. 294 00:22:11,833 --> 00:22:13,964 It's so much fun if you can get it. 295 00:22:14,204 --> 00:22:17,236 So yeah, so we're in booth one, two, three in the Startup Alley. 296 00:22:17,236 --> 00:22:18,532 So come see us. 297 00:22:18,532 --> 00:22:19,002 Awesome. 298 00:22:19,002 --> 00:22:30,259 Yeah, we did when we were first finding our way in legal back in our predecessor company, we were called Acrowire and I'm a former Microsoft guy and just kind of started consulting 299 00:22:30,259 --> 00:22:32,900 on the side as a lot of tech people do. 300 00:22:32,900 --> 00:22:36,212 And then the side gig started making more than the day job. 301 00:22:36,212 --> 00:22:39,284 So I quit and uh terrible timing. 302 00:22:39,284 --> 00:22:47,108 This was like right after the financial crisis, but I had enough client work to keep me busy and my bait, my bills paid. 303 00:22:47,260 --> 00:23:00,065 So I jumped in and we fell down the legal rabbit hole early and we didn't really know where our skills mapped on the, on the kind of the market spectrum in terms of size. 304 00:23:00,065 --> 00:23:13,411 we are our first show was like ABA tech show and it's great for kind of solo and small firms, but for big firms really ill to legal week, those are, those are better fits for, 305 00:23:13,411 --> 00:23:15,852 for our audience, which is, which is large law. 306 00:23:15,852 --> 00:23:17,270 Um, 307 00:23:17,270 --> 00:23:21,922 our first experience in legal tech was just a few months after launching. 308 00:23:21,922 --> 00:23:28,715 We were uh a finalist for one of the legal week awards. 309 00:23:28,955 --> 00:23:30,836 Wow, that was amazing. 310 00:23:30,836 --> 00:23:33,087 Cause we had never been to anything like that. 311 00:23:33,087 --> 00:23:41,360 And then to walk into that venue down there at the Hyatt, I thought the Hilton, the Hilton in New York, was like, holy smokes. 312 00:23:41,360 --> 00:23:43,932 Like this is, this is big time. 313 00:23:43,932 --> 00:23:45,117 It was pretty cool. 314 00:23:45,117 --> 00:23:45,709 Yeah. 315 00:23:45,709 --> 00:23:47,663 that was back when Stephanie Wilkins was running it. 316 00:23:47,663 --> 00:23:48,253 was awesome. 317 00:23:48,253 --> 00:23:49,193 Yeah. 318 00:23:49,193 --> 00:23:49,654 Yeah. 319 00:23:49,654 --> 00:23:52,094 mean, legal week is an interesting one for us. 320 00:23:52,094 --> 00:24:03,359 We, we attend every year, but it, you know, historically has been e-discovery focused and I, you know, I know they've tried to move beyond that in recent years, but we go, we 321 00:24:03,359 --> 00:24:04,699 don't, we don't exhibit. 322 00:24:04,699 --> 00:24:09,741 Um, the exhibit hall is very disjointed. 323 00:24:09,741 --> 00:24:17,584 Um, like, you know, it's, there's all little sorts of nooks and crannies and, um but we always make an appearance at legal week. 324 00:24:18,385 --> 00:24:19,204 for 325 00:24:19,367 --> 00:24:20,097 it's a good one. 326 00:24:20,097 --> 00:24:30,606 And then the one that I really liked a lot was very different, completely at other end of the scale, which is the LSC ITC, which is the Legal Services Council, right? 327 00:24:30,606 --> 00:24:34,089 So that was all about access to justice stuff. 328 00:24:34,089 --> 00:24:35,220 So that was really cool. 329 00:24:35,220 --> 00:24:40,154 was kind of, Bob Brogy wrote a really interesting piece last year about it, about the difference. 330 00:24:40,154 --> 00:24:48,340 Like he went from one to the other and he was like, wow, just that shows the gulf in certain resources and the two ends of the... 331 00:24:48,366 --> 00:24:49,296 cool, so to speak. 332 00:24:49,296 --> 00:24:50,097 Interesting. 333 00:24:50,097 --> 00:24:51,958 Well, I'm curious. 334 00:24:51,958 --> 00:24:54,619 She had mentioned the group out of Oakland. 335 00:24:54,619 --> 00:24:57,300 Are they? 336 00:24:57,300 --> 00:24:57,551 Yeah. 337 00:24:57,551 --> 00:24:57,851 Yeah. 338 00:24:57,851 --> 00:25:01,703 So is that an academic institution? 339 00:25:01,703 --> 00:25:03,444 Like who's behind that? 340 00:25:03,798 --> 00:25:05,679 Yeah, so they're nonprofit. 341 00:25:05,679 --> 00:25:09,822 They're run by a guy named Michael Listener, who's great. 342 00:25:09,822 --> 00:25:11,262 So hi, Michael, if you're listening. 343 00:25:11,262 --> 00:25:15,785 um And they are, um like I say, they're a nonprofit. 344 00:25:15,785 --> 00:25:18,577 they are very mission driven. 345 00:25:18,577 --> 00:25:24,851 I'm sure that they've got all kinds of academics involved with them and sort of on their board and things like that. 346 00:25:24,851 --> 00:25:29,593 But they're a straight up nonprofit, which means that they are... 347 00:25:29,593 --> 00:25:31,174 ah 348 00:25:31,478 --> 00:25:35,183 sort of at the source powering a lot of the legal tech innovation. 349 00:25:35,183 --> 00:25:39,729 And of course, they're not going to say publicly who their clients are unless they're like us. 350 00:25:39,729 --> 00:25:42,142 And we're always willing to say we're their client. 351 00:25:42,142 --> 00:25:50,479 You would scratch the surface on a lot of these startups and you would see that's where their data is coming from, for sure. 352 00:25:50,479 --> 00:26:04,724 with these types of organizations out there working hard to kind of open source uh legal information, does that open the door to challenge, you know, what's largely a duopoly, 353 00:26:04,724 --> 00:26:10,859 feels like, with Westlaw and Lexis with solutions, does that open the door for that? 354 00:26:12,798 --> 00:26:13,279 Yes. 355 00:26:13,279 --> 00:26:13,629 Yes. 356 00:26:13,629 --> 00:26:16,060 So yes and no, depending on how you look at it. 357 00:26:16,060 --> 00:26:18,842 So broadly speaking, absolutely. 358 00:26:18,842 --> 00:26:20,943 Like for sure. 359 00:26:20,943 --> 00:26:29,568 Like if anything is going to challenge those duopolies and those extraordinarily powerful companies, it's AI. 360 00:26:29,568 --> 00:26:29,988 Right? 361 00:26:29,988 --> 00:26:38,182 mean, that is the moment is here, you and they know that and that's why they're building so fast and acquiring so quickly and you know, all this stuff. 362 00:26:38,182 --> 00:26:39,573 there's no question. 363 00:26:39,573 --> 00:26:39,873 Right. 364 00:26:39,873 --> 00:26:41,742 And we've seen some really interesting 365 00:26:41,742 --> 00:26:46,822 things happening like with Villex and Cleo and know, Harvey and Lexus. 366 00:26:46,822 --> 00:26:50,562 So everyone's paying attention to this, as you certainly know, right, Ted? 367 00:26:50,562 --> 00:26:53,542 Because you do, you're a podcast, you talk about this a lot. 368 00:26:54,442 --> 00:26:57,662 But where it also opens the door. 369 00:26:57,682 --> 00:26:59,342 So that's like one end of the market, right? 370 00:26:59,342 --> 00:27:08,322 So and a lot of people, if not almost all people are aiming for the exact same part of the market, right? 371 00:27:08,322 --> 00:27:10,782 So the well-served... 372 00:27:11,180 --> 00:27:13,072 the places and this is fine. 373 00:27:13,072 --> 00:27:14,122 They need their tools. 374 00:27:14,122 --> 00:27:14,563 This is great. 375 00:27:14,563 --> 00:27:16,274 I have nothing, no digs or anything. 376 00:27:16,274 --> 00:27:21,709 But if everybody's always aiming for the same part of the market, there's not going to be a lot of innovation, right? 377 00:27:21,709 --> 00:27:25,442 That's not where things are going to get exciting, at least from my point of view. 378 00:27:25,442 --> 00:27:32,968 My point of view and the way we focus at Describe is how about that gigantic, unserved market, right? 379 00:27:32,968 --> 00:27:37,590 And I think it was, I don't want to misquote him, but I'm pretty sure it was Jack Newton. 380 00:27:37,590 --> 00:27:40,984 It was Jack Newton from Clio who said, um 381 00:27:40,984 --> 00:27:47,218 that there was maybe, I think it was like a trillion dollars of unmet need in the legal services industry. 382 00:27:47,218 --> 00:27:58,166 Now we better fact check that or, you know, I might get a letter from Uncle Leo saying that was wrong, but regardless, there's an enormous amount of unmet need out there for 383 00:27:58,166 --> 00:28:00,148 legal services, legal information. 384 00:28:00,148 --> 00:28:06,512 So when we were first starting out, uh we thought to ourselves, we could be a nonprofit, right? 385 00:28:06,512 --> 00:28:09,806 We could probably be a very successful nonprofit. 386 00:28:09,806 --> 00:28:13,386 if we wanted to be, we could get grants, we could do all sorts of things. 387 00:28:13,386 --> 00:28:16,266 But we always said, nope, we're a business. 388 00:28:16,906 --> 00:28:17,626 We're a business. 389 00:28:17,626 --> 00:28:29,346 And while we have a mission-driven focus, we are trying to create a very successful and sustainable and profitable business because AI allows us to offer very high quality tools 390 00:28:29,346 --> 00:28:35,526 that you could have not even imagined just a few years ago could possibly exist without human intervention. 391 00:28:37,870 --> 00:28:45,087 put it out there at a price that is so absurdly low compared to the competitors that we're just gonna gobble up how much of market share. 392 00:28:45,087 --> 00:28:46,748 that's the goal. 393 00:28:46,748 --> 00:28:54,666 So while we do like to present ourselves and we are mission driven, we have a very serious market driven approach to what we're doing. 394 00:28:54,666 --> 00:29:00,231 um And it's really starting to come to fruition now that we have a paid tool. 395 00:29:00,231 --> 00:29:03,946 em So I think there's huge opportunity, but I think... 396 00:29:03,946 --> 00:29:15,923 I would caution other people who are looking at this space, don't automatically assume you have to compete, you know, with Harvey, with Lexus directly, with Vlex, you know, that's 397 00:29:15,923 --> 00:29:16,954 not easy, right? 398 00:29:16,954 --> 00:29:18,715 And they're, those are very well funded firms. 399 00:29:18,715 --> 00:29:24,148 So look at other parts of the market where other people aren't looking at it and see what you can do there. 400 00:29:24,424 --> 00:29:34,090 Yeah, you know, I candidly, I've talked about this publicly before and I don't know, it may ruffle some feathers, the, what, what? 401 00:29:34,090 --> 00:29:34,380 Yeah. 402 00:29:34,380 --> 00:29:36,001 I mean, I'm not for everybody. 403 00:29:36,001 --> 00:29:38,252 know that my opinions don't res. 404 00:29:38,792 --> 00:29:39,672 Yeah. 405 00:29:40,133 --> 00:29:40,563 Yeah. 406 00:29:40,563 --> 00:29:41,244 Feather ruffle it. 407 00:29:41,244 --> 00:29:41,444 Yeah. 408 00:29:41,444 --> 00:29:52,275 I've ruffled a few feathers, um, in my day and, um, not intentionally, but I feel like just being candid and if, you know, if people get offended, then they do, but 409 00:29:52,275 --> 00:29:56,788 You know, I, we have really struggled on the smaller end of the market with, within the law firm world. 410 00:29:56,788 --> 00:30:01,812 Um, a lot of people call mid-law like 50 to like 150 lawyers. 411 00:30:01,812 --> 00:30:04,573 That's that really feels like small law for us. 412 00:30:04,573 --> 00:30:08,096 So, um, our market is really a hundred attorneys and up. 413 00:30:08,096 --> 00:30:13,129 And there are about 400 of those law firms in North America, which is our focus. 414 00:30:13,129 --> 00:30:20,530 We're doing some business in the UK now too, but by my estimates and there's no good numbers, there's only about 600 law firms on planet earth. 415 00:30:20,530 --> 00:30:22,381 who have more than a hundred attorneys. 416 00:30:22,381 --> 00:30:35,304 There are tens of thousands, if not hundreds of thousands of solo and smaller firms in that it's a very kind of, um, I guess steeply sloping pyramid. 417 00:30:35,304 --> 00:30:38,625 Um, yeah, that's a good way to describe it. 418 00:30:38,625 --> 00:30:41,465 Um, but it's really hard to do business there. 419 00:30:41,566 --> 00:30:50,578 And the reason it's hard to do business there as a tech company is because law firms historically have not valued, not seen tech as strategic. 420 00:30:50,828 --> 00:30:56,110 Um, and, and, mean, that's just the fact, like people can say what they want. 421 00:30:56,110 --> 00:30:58,351 I've been in this space 20 years. 422 00:30:58,351 --> 00:31:04,874 I know it to be true that that has been the historical perspective in the law firm world that is changing. 423 00:31:04,874 --> 00:31:07,945 And there are, and there are outliers where that is not true. 424 00:31:07,945 --> 00:31:17,649 And I, and I get that, but in the smaller, in the smaller end of the market, the things that we've struggled with are, um, a lack of sophistication from a technical perspective, 425 00:31:17,649 --> 00:31:20,500 you know, they could be rock stars on the. 426 00:31:20,500 --> 00:31:32,643 practice side, but a lot of times in that hundred attorney and under world, you'll have an IT director who, um, Kate, who was a, their former network administrator did a good job. 427 00:31:32,643 --> 00:31:35,064 So they got reported and now they're, you know what I mean? 428 00:31:35,064 --> 00:31:39,685 And there's nothing wrong with that, but it's, it's we. 429 00:31:40,266 --> 00:31:40,776 Right. 430 00:31:40,776 --> 00:31:41,986 Yeah, exactly. 431 00:31:41,986 --> 00:31:48,711 And so there's just been a lack of technical sophistication and you know, there's also a lot of, I got to 432 00:31:48,711 --> 00:31:50,592 a really good friend of mine who here in St. 433 00:31:50,592 --> 00:31:54,855 Louis, he owns a 50 attorney law firm and we play golf together. 434 00:31:54,855 --> 00:32:06,493 you know, I had, he asked me for somebody to go speak at his retreat and I teed a couple of people up and he was complaining about the price. 435 00:32:06,493 --> 00:32:12,197 I'm like, dude, you are lucky that this person is even giving you their attention, right? 436 00:32:12,197 --> 00:32:16,460 They normally speak in front of hundreds of thousands of people. 437 00:32:16,476 --> 00:32:27,089 Like that's, that's a bargain, but you know, it's an all small businesses, including us, when you're every dollar matters, you got, really have to manage your spend. 438 00:32:27,089 --> 00:32:36,870 But when you have limited budget combined with an audience who doesn't see tech as strategic, it's a really difficult market to sell into as a tech company. 439 00:32:37,218 --> 00:32:42,502 completely, but those people are also in very serious peril. 440 00:32:42,923 --> 00:32:43,323 Right? 441 00:32:43,323 --> 00:32:45,665 Like, and we're talking like a long arc here. 442 00:32:45,665 --> 00:32:56,694 So you're right for like individual companies, like can, can potential customers adapt fast enough to keep us sustainable and keep us going like for sure, like on an individual 443 00:32:56,735 --> 00:33:03,340 or even like a market, like a current market level, like you could argue that the change is going to be too slow and all that. 444 00:33:03,340 --> 00:33:05,942 But if you look at like a broader arc, 445 00:33:06,286 --> 00:33:08,466 this is not going to stay the same. 446 00:33:08,466 --> 00:33:13,766 Like think about sort of how we get our medical care now, right? 447 00:33:13,766 --> 00:33:15,846 And how much that has changed. 448 00:33:15,846 --> 00:33:32,786 And if you had a doctor's office, say, who refused to do e-charts or refused to meet with you online or refused to take your prescriptions through the portal versus calling. 449 00:33:32,786 --> 00:33:35,724 it's just, and medical is another weird. 450 00:33:35,724 --> 00:33:41,108 you want to, but like people, couldn't survive, right? 451 00:33:41,108 --> 00:33:42,079 You couldn't survive. 452 00:33:42,079 --> 00:33:52,388 so law probably has the wrong impression that they don't, there's some people who think that they adapt, they don't have to adapt in the same way. 453 00:33:52,388 --> 00:33:53,609 And there's a lot of resistance. 454 00:33:53,609 --> 00:33:58,563 And, for sure, one of the dumb jokes we tell, and we have many, is that when we're like, what should we build? 455 00:33:58,563 --> 00:34:05,198 Let's find the uh part of the economy where people are most, you know, 456 00:34:05,198 --> 00:34:08,518 open to risk and they love technology and they just are ready to share. 457 00:34:08,518 --> 00:34:10,178 We're like, wow, perfect. 458 00:34:10,178 --> 00:34:12,298 know, talk about what could we have picked that was harder? 459 00:34:12,298 --> 00:34:13,918 I can't even imagine. 460 00:34:13,978 --> 00:34:19,658 But I do think we're at a point where no matter what it has to change. 461 00:34:19,658 --> 00:34:29,658 can't have the triangulation we have right now with the advent of AI and just how fundamentally that's going to change everything we do soup to nuts. 462 00:34:29,658 --> 00:34:30,018 Right. 463 00:34:30,018 --> 00:34:35,318 And then you have a vastly underserved part of the market. 464 00:34:35,648 --> 00:34:42,594 and then of extraordinarily overpriced legacy providers, like that's gonna implode, right? 465 00:34:42,594 --> 00:34:55,155 And so the smart attorneys out there, and they're all smart, no offense, the tech forward and the forward thinking attorneys are gonna have to figure out how to adapt to this or 466 00:34:55,155 --> 00:35:00,039 they're gonna see their share of the market, know, start to crater. 467 00:35:00,039 --> 00:35:03,372 And the new students who are going through law school and learning this stuff, 468 00:35:03,372 --> 00:35:05,267 are gonna come out with different expectations too. 469 00:35:05,267 --> 00:35:09,234 So there'll be a fight for talent as well. 470 00:35:09,234 --> 00:35:10,315 Yeah, no, for sure. 471 00:35:10,315 --> 00:35:16,989 Yeah, that kind of legacy mindset is incompatible with where we're going. 472 00:35:16,989 --> 00:35:25,075 It's just, I know so many firms that are going to struggle to adapt and not necessarily some small firms. 473 00:35:25,075 --> 00:35:30,838 I know of an Amlaw firm who I'm really good friends with, the chief knowledge officer there. 474 00:35:31,524 --> 00:35:32,940 And, um 475 00:35:33,402 --> 00:35:39,658 I was working on a project with her for a presentation and she was completely dark in January. 476 00:35:39,658 --> 00:35:41,066 And I was like, where have you been? 477 00:35:41,066 --> 00:35:42,851 She's like, I've been working on a DMS upgrade. 478 00:35:42,851 --> 00:35:44,103 I'm like, DMS? 479 00:35:44,103 --> 00:35:44,733 You've been working? 480 00:35:44,733 --> 00:35:46,035 I was like, that's IT. 481 00:35:46,035 --> 00:35:46,895 What's the chief knowledge? 482 00:35:46,895 --> 00:35:48,387 She's like, I am IT. 483 00:35:48,387 --> 00:35:49,407 And I am KM. 484 00:35:49,407 --> 00:35:56,875 And it's like, OK, your firm has set you up for failure if you're going to be promoting knowledge and innovation. 485 00:35:57,176 --> 00:35:57,474 Yeah. 486 00:35:57,474 --> 00:35:59,266 strategic error on their part. 487 00:35:59,266 --> 00:36:05,501 And you know, maybe this dovetails back to the conversation we were having about benchmarking too, right? 488 00:36:05,501 --> 00:36:13,102 Because the risks for firms too, and for, you know, uh any size firm is huge if they pick the wrong tool. 489 00:36:13,237 --> 00:36:23,305 It's huge if they rely on something that's spotty, you know, that's, and that's why the momentum is hard to change with the big trusted companies because I get it. 490 00:36:23,305 --> 00:36:24,470 I mean, if I'm... 491 00:36:24,470 --> 00:36:29,214 you know, working at some firm and I'm in charge of their IT and making sure they have the right tools. 492 00:36:29,214 --> 00:36:32,617 I'm not really interested in some, you know, brand new startup. 493 00:36:32,617 --> 00:36:34,769 Like that's, that's scary, right? 494 00:36:34,769 --> 00:36:36,400 That's, that's super scary. 495 00:36:36,400 --> 00:36:41,665 So again, there's a comeback to where, where can the industry provide a little more reassurance? 496 00:36:41,665 --> 00:36:43,516 I think it's useful for all of us. 497 00:36:43,516 --> 00:36:46,863 Yeah, well you've had some validation. 498 00:36:46,863 --> 00:36:52,694 talk a little bit about the case text and law school curricula and what you guys are doing there. 499 00:36:52,909 --> 00:36:54,610 Yeah, so this is really fun. 500 00:36:54,610 --> 00:36:58,430 this was this actually happened at the tech show. 501 00:36:58,970 --> 00:37:00,370 it's always good to self. 502 00:37:00,370 --> 00:37:04,550 It's always good to show up at these things when you're when you're new, because you never know who you're going to meet. 503 00:37:05,190 --> 00:37:08,530 So we, as folks know, have been listening. 504 00:37:08,530 --> 00:37:09,890 have case law research. 505 00:37:09,890 --> 00:37:16,530 It's we have free access and we have a paid tool, $10 a month and $20 a month, depending on the level. 506 00:37:16,530 --> 00:37:18,810 So paid, but almost free. 507 00:37:18,810 --> 00:37:19,510 Right. 508 00:37:19,510 --> 00:37:20,410 So 509 00:37:21,142 --> 00:37:29,889 The uh legal tech curriculum is from, hang on, I'm just gonna get the exact right terminology here so I'm not saying the wrong thing. 510 00:37:29,889 --> 00:37:43,008 So we will be rolling out into uh over 350 law schools uh internationally this fall as part of a legal curriculum that is from the National Society for Legal Technology and will 511 00:37:43,008 --> 00:37:45,379 be part of their legal research curriculum. 512 00:37:45,379 --> 00:37:49,442 And what's really fun about this is that we are replacing case text 513 00:37:49,502 --> 00:38:00,140 in their um curriculum because case tax no longer, now that they've been acquired for 650 million, you good for them, um they don't have free access any longer. 514 00:38:00,140 --> 00:38:02,192 I think that was turned off in March. 515 00:38:02,192 --> 00:38:06,405 So we will be replacing uh our friends at Case Tax in the curriculum. 516 00:38:06,405 --> 00:38:14,171 And so we will be included with Lexis Plus, Westlaw, Bloomberg Law, Fast Case, and HeinOnline, and us, and Describe. 517 00:38:14,171 --> 00:38:16,192 So it does show that 518 00:38:16,415 --> 00:38:18,846 I guess, uh validation of the tool. 519 00:38:18,846 --> 00:38:31,164 um Doug Lusk from the CEO from uh the, NSLT said, you know, we were his favorite and he was very impressed with what we were building. 520 00:38:31,164 --> 00:38:34,536 So that was some big validation for us. 521 00:38:34,536 --> 00:38:45,932 um Another nice piece of validation we had recently was Bob Enroji covered our AI citator release and said we were now poised to meaningfully 522 00:38:45,998 --> 00:38:50,741 uh be thought of as a competitor for the big legal research tools. 523 00:38:50,741 --> 00:38:52,112 So these are pretty exciting things. 524 00:38:52,112 --> 00:38:56,966 And again, good luck of having having done this without AI. 525 00:38:56,966 --> 00:38:59,608 It's quite literally would not have been possible. 526 00:38:59,608 --> 00:39:09,554 So we're kind of the poster child for what, how nimble and lean and sort of creative AI companies can be, which is pretty cool. 527 00:39:10,595 --> 00:39:11,536 Thank you. 528 00:39:11,536 --> 00:39:12,957 We're very excited. 529 00:39:14,098 --> 00:39:14,750 Yeah. 530 00:39:14,750 --> 00:39:17,180 So an interesting thing happened this week. 531 00:39:17,180 --> 00:39:19,671 So we are a TLTF portfolio company. 532 00:39:19,671 --> 00:39:28,753 um one of the directors over there tagged uh me and a few others in the post, Tom Baldwin from Ennegrata. 533 00:39:28,954 --> 00:39:37,296 And uh a VC had written a future of law um kind of 534 00:39:38,037 --> 00:39:40,157 Manifesto and it's so good. 535 00:39:40,157 --> 00:39:41,617 Like I, I agree. 536 00:39:41,617 --> 00:39:42,977 It's a, it's, they're called catalyst. 537 00:39:42,977 --> 00:39:45,637 I'd really, I'd never heard of them prior to that. 538 00:39:45,637 --> 00:39:53,457 Maybe we can create a link in the show notes, but they mentioned info dash and like as an, company they're excited about. 539 00:39:53,477 --> 00:40:00,893 Um, and I, know, I get like 15, I'm not exaggerating 15 to 20 emails from VCs a week. 540 00:40:00,893 --> 00:40:04,694 LinkedIn messages, they call, I don't know how they have my cell phone number, but they do. 541 00:40:04,694 --> 00:40:10,455 And it's, I'm flattered, but I could fill up my calendar with just talking to them and we don't need money. 542 00:40:10,455 --> 00:40:20,958 Like we're V we're, um, we're, bootstrapped and we took a little bit of funding from TLTF, not really for the funding, but just because the working with them is amazing. 543 00:40:20,958 --> 00:40:23,208 Um, they are. 544 00:40:23,208 --> 00:40:24,399 Yeah. 545 00:40:24,399 --> 00:40:25,759 They, they can open doors. 546 00:40:25,759 --> 00:40:26,859 They know the market. 547 00:40:26,859 --> 00:40:29,122 It's, it's a, it's a really good relationship. 548 00:40:29,122 --> 00:40:33,589 Plus you get to go to their fun summit, which is always in really cool places. 549 00:40:34,592 --> 00:40:35,592 Yeah. 550 00:40:36,255 --> 00:40:38,094 Oh, Austin's the best, yeah. 551 00:40:38,094 --> 00:40:42,755 in like the Ritz Carlton and Fort Lauderdale and then last year in Key Biscayne. 552 00:40:42,795 --> 00:40:43,706 So it's really good. 553 00:40:43,706 --> 00:40:56,419 But you know, like, I think what is also interesting now with in terms of challengers to these big established players is now you have funds like TLTF that are completely zeroed 554 00:40:56,419 --> 00:40:59,124 in and you know, reading that 555 00:40:59,124 --> 00:41:09,927 Catalyst article about the future of law made me realize something I thought they were the VCs were hitting us up because we've had really strong growth and it's very visible on 556 00:41:09,927 --> 00:41:13,458 LinkedIn just by headcount So was like, that's why they're hitting us up. 557 00:41:13,458 --> 00:41:26,992 But after I read that I was like, oh there is a broader investment thesis that what we're doing aligns to and I never really I never realized how smart these funds are in 558 00:41:26,992 --> 00:41:29,062 understanding like 559 00:41:29,929 --> 00:41:33,822 these are some of the smartest people ever go into these spaces. 560 00:41:33,822 --> 00:41:39,398 And VCs, boy, their whole value prop is upside down right now. 561 00:41:39,398 --> 00:41:42,371 So they're trying to figure out how to survive too, right? 562 00:41:42,371 --> 00:41:44,053 Because AI is flipping everything. 563 00:41:44,053 --> 00:41:47,126 You don't need those kinds of big investments anymore for engineering. 564 00:41:47,287 --> 00:41:50,802 So they're nervous. 565 00:41:50,802 --> 00:41:55,323 a lot of money on the sideline that needs to find a home and it's kind of their job to do it. 566 00:41:55,323 --> 00:42:00,344 this was written like I wrote it and I've been in the space 20 years. 567 00:42:00,344 --> 00:42:02,305 I host a podcast on it. 568 00:42:02,305 --> 00:42:03,655 I speak at conferences. 569 00:42:03,655 --> 00:42:11,317 I attend conferences and this VC wrote what I thought was a fantastic outlook for where legal is going. 570 00:42:11,317 --> 00:42:12,968 So anyway, we were... 571 00:42:13,328 --> 00:42:13,862 yeah. 572 00:42:13,862 --> 00:42:14,774 guys send me a link. 573 00:42:14,774 --> 00:42:15,554 really good. 574 00:42:15,554 --> 00:42:16,805 It's really good. 575 00:42:16,945 --> 00:42:26,330 But so how does a of a bootstrapped company, you know, a two person bootstrap company go about competing with these? 576 00:42:26,330 --> 00:42:27,690 I mean, you've told your story. 577 00:42:27,690 --> 00:42:29,671 Is your story repeatable? 578 00:42:29,671 --> 00:42:31,872 is that a playbook people can use? 579 00:42:32,174 --> 00:42:33,734 I mean, yes and no. 580 00:42:33,734 --> 00:42:36,694 here's the other kind of thing that's cool. 581 00:42:36,694 --> 00:42:44,034 Like everybody always thinks that 20 whatever year old, you know, startup people are magic and they are. 582 00:42:44,154 --> 00:42:51,914 But when you're a startup founder in a different part of your career, later in your career, you can kind of do things a little differently too. 583 00:42:51,914 --> 00:42:58,154 Like hopefully you have a little bit of your own money you can invest or you have a little more, you know, ability to kind of do it the way you want. 584 00:42:58,614 --> 00:43:00,800 I would say that, you know, 585 00:43:00,800 --> 00:43:02,151 depending on where you are in your life. 586 00:43:02,151 --> 00:43:06,134 um Because, you know, we did invest in it, right? 587 00:43:06,134 --> 00:43:10,918 We invested time and, you know, it's not like open AI was giving us free credits, you know what I mean? 588 00:43:10,918 --> 00:43:16,453 Like, so there was some significant investment, but, we invested it ourselves, right? 589 00:43:16,453 --> 00:43:26,061 And so since we didn't have to pay for engineering, which is really expensive, and we didn't have to pay for marketing, which is also really expensive, like we saved a ton of 590 00:43:26,061 --> 00:43:26,251 money. 591 00:43:26,251 --> 00:43:30,794 So I say, yes, it's repeatable um for the right 592 00:43:31,288 --> 00:43:32,688 people, if that makes sense. 593 00:43:32,688 --> 00:43:42,341 you kind of, have to have some of your own resources and you have to be tenacious as hell. 594 00:43:42,341 --> 00:43:43,079 You know what I mean? 595 00:43:43,079 --> 00:43:44,942 It's like, it is hard. 596 00:43:45,022 --> 00:43:47,262 It is hard, but it is fun. 597 00:43:47,342 --> 00:43:52,784 and I do, did you, I used to not have gray hair. 598 00:43:53,064 --> 00:43:54,744 So there you go. 599 00:43:54,744 --> 00:44:00,638 But I also think, and this is like a bit esoteric, so forgive me, but I do also think AI, 600 00:44:00,706 --> 00:44:12,029 We talk about this on the show a lot with VCs and stuff like, I think AI is going to also help us think about different ways we fund things because right now we have like a very 601 00:44:12,029 --> 00:44:13,729 broken model, I think. 602 00:44:13,850 --> 00:44:21,672 And this is where state governments, if they're smart, they're going to start to step in and things like that, which, you know, smart government can be like maybe a a big ask. 603 00:44:21,672 --> 00:44:29,814 But, you know, we have, we have, if you're a nonprofit and you want to go the full altruistic route, there's resources for you to build. 604 00:44:29,814 --> 00:44:30,456 Right. 605 00:44:30,456 --> 00:44:33,888 There's grants, there's foundations, there's all kinds of stuff. 606 00:44:33,888 --> 00:44:39,198 If you want to go the full, I'm going to charge as much as I possibly can for my product and make as much money as possible. 607 00:44:39,198 --> 00:44:43,693 So someone wants to buy me and I have an exit, we have a model for that, right? 608 00:44:43,693 --> 00:44:51,728 A model like ours where we're like, I could be charging 30 times more for what we have, but I'm not because I'm trying to do something that's in between. 609 00:44:51,728 --> 00:44:53,779 It's like a social entrepreneurship, whatever. 610 00:44:53,779 --> 00:44:59,394 There's very limited money structures, support, even thinking around. 611 00:44:59,394 --> 00:45:04,358 how to build there and that's sad because that is where there's so much opportunity. 612 00:45:04,358 --> 00:45:15,005 So I think like the challenge and the call I will put out if there's any politicos or like people in any space to think about this, like there's a real opportunity there to rethink 613 00:45:15,005 --> 00:45:21,570 how we even fund ah sort of disruptive technologies right now. 614 00:45:21,692 --> 00:45:23,183 Yeah, no, that's a great point. 615 00:45:23,183 --> 00:45:33,559 mean, you know, uh VCs, PE, growth equity, all of these funding models have to generate return for their investment. 616 00:45:33,559 --> 00:45:41,234 And if you're leaving money on the table, which you are intentionally, it's, it's, I don't know that that's the right fit for them. 617 00:45:41,494 --> 00:45:44,035 No, they think they don't understand. 618 00:45:44,035 --> 00:45:47,577 It's truly bizarre to them. 619 00:45:49,198 --> 00:45:57,411 But they're going to have to adapt because the model for what people are building is going to change and they're going to be left out because people aren't going to take their money 620 00:45:57,411 --> 00:45:59,353 and then jack their prices off. 621 00:45:59,353 --> 00:46:02,645 And the younger generations want to make meaningful change. 622 00:46:02,645 --> 00:46:04,206 They don't want to just be rich. 623 00:46:04,206 --> 00:46:05,146 Some do. 624 00:46:05,192 --> 00:46:05,843 it's true. 625 00:46:05,843 --> 00:46:06,143 Yeah. 626 00:46:06,143 --> 00:46:10,299 mean, rich can be, you know, a byproduct of just doing good things. 627 00:46:10,299 --> 00:46:13,063 Um, that's the hope, right? 628 00:46:13,063 --> 00:46:13,762 And 629 00:46:13,762 --> 00:46:23,994 Yeah, they call it in Massachusetts, our former Secretary of Economic Development, um Yvonne Howe used to call it, do well by doing good. 630 00:46:24,295 --> 00:46:25,535 I love that. 631 00:46:25,576 --> 00:46:27,149 There's no reason you can't have both. 632 00:46:27,149 --> 00:46:28,000 It makes sense. 633 00:46:28,000 --> 00:46:34,752 mean, you know, there are, could go take some funding and probably go grow a heck of a lot faster and probably end up at a bigger payday. 634 00:46:34,752 --> 00:46:35,263 But you know what? 635 00:46:35,263 --> 00:46:36,453 I love what I do. 636 00:46:36,453 --> 00:46:37,901 I'm growing incrementally. 637 00:46:37,901 --> 00:46:40,425 I mean, we're having over a hundred percent year over year growth. 638 00:46:40,425 --> 00:46:43,736 It's not like it's slow, but I'm enjoying it. 639 00:46:43,736 --> 00:46:53,724 I like having some VC breathing down my neck telling me I got to push harder or I have to, you know, fire people that aren't meeting these criteria. 640 00:46:54,114 --> 00:46:55,576 Or you get bumped out, right? 641 00:46:55,576 --> 00:46:56,892 They're like, oh, nevermind. 642 00:46:56,892 --> 00:46:57,806 Thanks for building this. 643 00:46:57,806 --> 00:46:58,278 Bye bye. 644 00:46:58,278 --> 00:46:59,299 Right, exactly. 645 00:46:59,299 --> 00:47:03,371 And that's just not, I'm at a stage in my life where I don't need to do that. 646 00:47:03,371 --> 00:47:05,752 And I'm just having a lot of fun. 647 00:47:05,752 --> 00:47:07,373 My reputation matters to me. 648 00:47:07,373 --> 00:47:13,163 I want to deliver great work to people and hold my head high when I walk around a legal tech conference, you know. 649 00:47:13,163 --> 00:47:15,386 Maybe we need our own organization, Ted. 650 00:47:15,386 --> 00:47:19,730 Maybe like these stubborn GenX boot strappers. 651 00:47:19,730 --> 00:47:23,496 We need our own little conference. 652 00:47:23,496 --> 00:47:34,894 You know what I have thought about honestly, in the past, some sort of like, um, model with which vendors could kind of organize and collaborate. 653 00:47:34,894 --> 00:47:37,456 And I haven't figured out how to do that yet. 654 00:47:37,456 --> 00:47:41,969 And I'm so busy with my day job, but, um, I started a franchisee association. 655 00:47:41,969 --> 00:47:43,970 My wife and I own five gyms here in St. 656 00:47:43,970 --> 00:47:51,295 Louis and, that brand needed some help on the franchisee side that we weren't getting from HQ. 657 00:47:51,295 --> 00:47:52,606 They're great, but. 658 00:47:52,606 --> 00:47:54,917 They were growing so fast, they weren't giving support. 659 00:47:54,917 --> 00:47:59,036 So I started a nonprofit and it was wildly successful. 660 00:47:59,036 --> 00:48:00,430 I handed over the keys. 661 00:48:00,430 --> 00:48:03,502 It's still doing great, but man, I got so much. 662 00:48:03,502 --> 00:48:05,222 created mentoring programs. 663 00:48:05,222 --> 00:48:08,743 We did a summit where we brought everybody together. 664 00:48:08,743 --> 00:48:12,806 uh We brought in speakers and it was great. 665 00:48:12,806 --> 00:48:13,867 That's not a bad idea. 666 00:48:13,867 --> 00:48:15,882 Maybe you and I should connect at Ilta. 667 00:48:15,882 --> 00:48:16,722 talk, yeah. 668 00:48:16,722 --> 00:48:26,305 And then we should encourage, from my branding perspective, we should encourage the big players to help fund this because we're going after markets they don't want anyway, or at 669 00:48:26,305 --> 00:48:27,186 least I am. 670 00:48:27,186 --> 00:48:35,848 So it can be like, fine, help the innovation economy, but don't worry, it's not people who want your customers and then they can look like the good guys in the room who are helping 671 00:48:35,848 --> 00:48:38,139 uh increase access to the law. 672 00:48:38,139 --> 00:48:39,688 There you go, boom, done. 673 00:48:39,688 --> 00:48:40,219 I like it. 674 00:48:40,219 --> 00:48:43,418 They won't they won't like me though because I am taking their market share. 675 00:48:43,418 --> 00:48:44,163 competing with them. 676 00:48:44,163 --> 00:48:45,724 Okay, but we'll keep you. 677 00:48:45,724 --> 00:48:46,864 You can be a silent person. 678 00:48:46,864 --> 00:48:48,608 Exactly, exactly. 679 00:48:48,608 --> 00:48:50,792 Well, this has been a great conversation. 680 00:48:50,792 --> 00:48:58,948 um Before we wrap up, just tell people how they can find more out about what you do, your podcasts, stuff like that. 681 00:48:59,278 --> 00:49:00,318 Yeah, great. 682 00:49:00,318 --> 00:49:04,378 So first of all, if you happen to be at Ilticon, come by the Startup Hub. 683 00:49:04,378 --> 00:49:07,338 Booth 123 will be hanging out and would love to meet you. 684 00:49:07,338 --> 00:49:09,098 You can always check out our website. 685 00:49:09,098 --> 00:49:14,618 It's describe with a Y because, you know, startups have to have weirdly spelled names. 686 00:49:14,878 --> 00:49:17,098 So describe.com with a Y. 687 00:49:17,098 --> 00:49:21,938 We're most active on LinkedIn, which is kind of like where the Legal Tech people hang out. 688 00:49:21,938 --> 00:49:23,698 So find me on there. 689 00:49:23,698 --> 00:49:25,398 Happy to connect. 690 00:49:25,738 --> 00:49:27,578 Ping us, stop by. 691 00:49:27,804 --> 00:49:32,132 the booth and yeah, just love to love to talk to people in the community. 692 00:49:32,132 --> 00:49:33,402 It's the best part of the job. 693 00:49:33,402 --> 00:49:33,882 Awesome. 694 00:49:33,882 --> 00:49:36,664 And InfoDash will be in booth 308 as well. 695 00:49:36,664 --> 00:49:39,836 So stop by there after you stop by describes. 696 00:49:39,836 --> 00:49:42,417 um Well, this has been a great conversation. 697 00:49:42,417 --> 00:49:44,408 I look forward to seeing you next week. 698 00:49:44,408 --> 00:49:46,799 And let's keep the conversation going. 699 00:49:47,042 --> 00:49:48,500 Great, thanks Ted, this was really fun. 700 00:49:48,500 --> 00:49:50,478 I'm so happy to have joined you, thank you. 701 00:49:50,478 --> 00:49:50,891 Awesome. 702 00:49:50,891 --> 00:49:51,877 You're very welcome. 703 00:49:51,877 --> 00:49:52,869 Take care. 704 00:49:53,420 --> 00:49:54,332 Bye bye. -->