#284 Pat Utz: Inside Abstract, The AI That Decodes Laws and Regulations

What if AI could decode government in real time? In this episode of Eye on AI, Craig Smith sits down with Pat Utz, CEO and Co-Founder of Abstract, the AI startup building "regulatory superintelligence" to track and analyze laws, bills, and regulations across 145,000+ government entities. Pat explains how Abstract evolved from university research into a venture-backed company helping law firms, enterprises, and policymakers cut through the noise of Congress, state legislatures, and regulatory agencies. From uncovering hidden amendments in massive bills to proactively identifying risks and opportunities for businesses, Abstract is transforming how we understand legislation. We cover: How AI is reshaping lobbying, law, and compliance Why Abstract is focused on proactive intelligence, not reactive compliance The role of AI agents, LLMs, and retrieval-augmented generation (RAG) in policy analysis Real examples of AI influencing funding and legislation The future of democracy when citizens and businesses have true transparency into government Whether you're in tech, law, government affairs, or just curious about how AI is changing democracy, this conversation reveals the future of policy intelligence. 🔗 Learn more about Abstract: https://www.abstract.us https://www.abstract.us?utm_source=chatgpt.com

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  We're scanning updates across these regulatory bodies and these legislative bodies. And we're using AI to figure out what's relevant for a law firm and their clients. Or in the case of a company, what's relevant to that company and their business units. The company has a big labor force. They have to understand how government is changing laws and codes as it pertains to their labor force. Right? The local, state and federal level. There's over 145,000 government entities in the US alone. You know, we're talking Congress all the way down to your local school district. Right? That school district is a government entity of itself. So our tech is going out and picking up any updates from these government websites.

• 0:43Speaker 00

  And also picking up signals from news and social media. Thank you for having me on, Craig. So my name is Pat. I'm one of the co-founders and CEO at Abstract. And we've been at this for about six years now. A little bit of background on us. We started in classical research in natural language processing back in 2019. Computer engineers and electrical engineers by trade. But really passionate about trying to make sense of laws and codes. Sort of bring transparency to the opaque, you know, legislating process. What ended up happening is we sort of got tapped on the shoulder by the head of entrepreneurship at Loyola Marymount University.

• 1:28Speaker 00

  And he said, hey, I think this research that you're doing can apply to people in the lobbying space. So we ended up spending about two and a half, three years selling a collaborative sort of stakeholder management tool for lobbyists. Worked with over 200 firms and then raised venture capital to expand to our current focus, which is, you know, mostly working with fake law firms and large companies with their legal teams, taking in all the changes across regulatory and legislative bodies. And using the reasoning capability of AI to distill what may be a risk or an opportunity to that business. So we've got, you know, we got a chance to really get a deep understanding of how the sausage is made.

• 2:14Speaker 00

  And, you know, sort of using AI to distill what's actually relevant across all of this.

• 2:19Craig S. Smith?

  Yeah, and and describe exactly um what what the the platform or product does. I've had um I had another company on.

• 2:32Craig S. Smith?

  Uh, probably four or five years ago, that's uh that that was using AI to uh identify targets for political fundraising, and I found that fascinating. Uh, but but this is specifically uh looking at the legislative process and and helping lobbyists. Uh, so how does how do describe how the product works?

• 3:02Speaker 00

  Yeah, so if you look at our government structure, it's sort of the classical three-tier structure, which is the executive branch, legislative branch, and the judicial branch. And we have a flavor of that at the federal level, the state level, and sometimes at the local level as well. So what we're focused on um right now is mostly the uh executive and the legislative branches. And that is in the form of legislative bodies, so think a state legislature or Congress. And specifically within those legislatures, it is the bill that is being introduced and amended to essentially create a new law or change an existing set of laws.

• 3:47Speaker 00

  And on the executive side, it's uh usually a regulatory agency, and they're introducing, you know, changes to the right, the the rules, right, that they've they've set out. Um, or which we've seen a lot of recently, um, their executive orders, right? Or governor orders at the state level. Um, so these are all sort of uh key parts of how government dictates what society does. And what we're doing at Abstract is we're scanning updates across these regulatory bodies and these legislative bodies. And we're using AI to figure out what's relevant for a law firm and their clients. Or in the case of a company, what's relevant to that company and their business units.

• 4:34Speaker 00

  The reason it matters is usually one of a couple of like key examples, which is usually product or labor, right? So if a company has a big labor force, they have to understand how government is changing laws and codes as it pertains to their labor force, right? The local, state and federal level. On the product side, you know, if you're in a financial services space as an example, you need to know what are the changes that may happen on the regulatory, you know, set of framework that may impact your product roadmap and your ability to sell right in a certain market. So increasingly, we see sort of those two

• 5:15Speaker 00

  sides. The last piece is taxes and finances. So how a government changes laws may impact a company's ability to actually sort of change their tax outlook. And that happens also at the local, state and federal level.

• 5:33Craig S. Smith?

  Yeah. And how do you do that? I mean, are you, well, first of all, let's go back to the original research before you guys were tapped and told this would be applicable to government. What was that research originally?

• 5:51Speaker 00

  Yeah. So the research was pre OLMs. And so we were working with classifiers. And, you know, we called it natural language processing. Very simply put, is the area subset of AI focused on processing natural language. So the idea was to use these classifiers to essentially take bills and, you know, legislation at Congress level and make summaries of it, right? Which is why we called it abstract. And the idea was actually to make a consumer application. We, we said, hey, if we can make summaries of these complicated bills, we can bring greater transparency to this, this process as a whole. And I think, you

• 6:34Speaker 00

  know, to this day, it still rings true in terms of our mission of making all this data more accessible for the everyday person. And even though we're a B to B company, right? We sell primarily to law firms and enterprises. I definitely think there is a path forward in the future for us to expand these services for the daily use case for, for each individual.

• 6:57Craig S. Smith?

  And, and does the platform track?

• 7:02Craig S. Smith?

  Everything that's published in, say, the Congressional Record? Or, or is it, uh, does it depend on a user uploading documents and, uh, asking for analysis?

• 7:16Speaker 00

  Yeah, so this is part of what took a while, uh, to build and develop expertise around. So there's over a hundred and forty-five thousand government entities in the U.S. alone. You know, we're talking Congress all the way down to your local school district, right? That school district is a government entity of itself. So our tech is going out and picking up any updates from these government websites. Um, and also picking up signals from news and social media. Uh, part of the unlock here, and I think this is going to transform the way a lot of this was, the work is done in other industries, is, uh, agents

• 8:00Speaker 00

  and their ability to go out and autonomously pick up these signals and process that, right? For an application. So that's been an unlock on our end, although we've been working on that for about three years now. Um, but yes, we're picking up all these signals and we've built that in-house.

• 8:17Craig S. Smith?

  And including the text of, uh, tabled bills or

• 8:23Craig S. Smith?

  those that are tabled, I mean, uh,

• 8:26Speaker 00

  Yeah, yeah. So, so the way it works is there's usually the existing set of codes and laws um, in that state, city, county, or federal entity. And then every year or every session, the legislature works on all of the proposed bills. And just for context, uh, you know, in California, there's about five to seven thousand bills a year. That's a lot of bills. Um, and there are oftentimes spot bills that are introduced, which have no language at all. And their primary focus is to just exist and just, just go through the process until the very end where they're gut and amended, which implies sort of what we hear right there.

• 9:12Speaker 00

  You know, the name might have to do with water rights, but it's gutted to be some sort of tax, um, amendment, right? So that's a very common process.

• 9:20Craig S. Smith?

  Yeah, I didn't know that. In other words, it's sort of like, uh,

• 9:26Craig S. Smith?

  What do they call that a SPAC or a what in Asia they call the backdoor listing where you you have an empty vessel that's listed and then you can you know, fill it with whatever you want. Is is that that right?

• 9:41Speaker 00

  That is what a SPAC bill is. Yes. And especially one that's gut and amended, uh, because it's gutted and amended to talk about something else. And that's one tactic. Another tactic and is using the budget or trailer bills to get a policy through. So the thing is that um, bills that need some sort of appropriation, they need some sort of budget to get something done. Um, they have to go through a separate process. And those bills end up being quite large in nature, um, sort of like this big, beautiful act or big, beautiful bill that we're seeing at the federal level. Um, and this is where, you know, lobbying firms, associations, elected officials, they take the opportunity to sort of add their amendments.

• 10:25Speaker 00

  Because um, on the legislative process, it's easier to get something through that big bill instead of sort of making a bill in of itself for that issue. And so all this information needs to be tracked. Historically, you know, a company or a nonprofit or a law firm had to hire, you know, people to actually read these bills and figure out what's relevant. From there, they would figure out a strategy if they want to lobby to change it or do nothing and let it become a compliance issue down the line. Um, but AI is fundamentally changing how we we think about this process as a whole.

• 11:09Craig S. Smith?

  Yeah. So, uh, but again, the uh, the big beautiful bill is an example. Does your platform pick that up once it's published?

• 11:20Craig S. Smith?

  Uh, or, or you're not relying on, on a user to upload it and ask questions about it.

• 11:27Speaker 00

  Correct. We're providing the data. We're scanning and monitoring that twice a day. So we have like millions of records every day coming in. Um, and then for each client, we then use that reasoning capability of these model to figure out what's actually relevant for each of them.

• 11:46Craig S. Smith?

  I see. Yeah. Can you, uh, on the, on the big beautiful bill, because a lot has been made, uh, of its various amendments. Um, and a lot, and it got so when will the few members of Congress have actually read the entire thing? Does it, is there a conversational interface then where you can ask questions about a specific piece of legislation like that bill? You can ask

• 12:16Speaker 00

  Yeah.

• 12:17Craig S. Smith?

  lists, uh, all of the, you know, the, the things have been added in, uh, that are not directly related to the budget, that sort of thing.

• 12:29Speaker 00

  Yeah. So that's a really core part of the, the workflow, which is asking deeper questions about the document. And especially relevant when the document is as large as that, the beautiful bill. Um, and sort of where, you know, we're building expertise is, uh, giving abstract that context on, okay, I am an expert at understanding public policy regulatory changes, right? Connecting that bill with other bills, other regulatory amendments. Cause if you look at governance as a whole, everything's connected, right? Even down to the judicial level. So all this is being done, um, with context on what the business does.

• 13:13Speaker 00

  And, uh, and, and that is a core part of, of sort of the value that we're, we're building with, without chart.

• 13:20Craig S. Smith?

  Yeah, and you said there is a conversational interface for the user?

• 13:25Speaker 00

  You can just ask questions like, hey, like, what part of this bill is relevant? Right? Can you highlight pieces I need to focus on? Right? So you don't have to read the bill itself. And we're seeing this sort of flow in other industries as well. And where AI is leveraged, you know, with some sort of industry expertise to analyze a dense document or dense data set.

• 13:49Craig S. Smith?

  Yeah. And for your analysis engine, is that a fine tuned model? Open source model, or are you hitting one of the proprietary models with an API? Or how do you manage that?

• 14:05Speaker 00

  Great question. So what I can say is like, we are pretty adamant about not building a custom model in-house. Just because our philosophy is such that the big foundational model companies like OpenAI, Anthropic, that's their focus. They're going to continue pouring millions, not billions into that. And we want to leverage benefits of that as they get better.

• 14:29Speaker 00

  So we are, though, fine tuning aspects of these models in-house. And then we're also pairing it with context on each business. There's a lot of work that's been done with retrieval augmented generation. And or, you know, what people call RAG. And that's just providing more documents that you're telling the model, just pick context from here. And don't hallucinate, right? This is sort of like your universe where you can reason. And there's a lot of frameworks being developed on that that are just getting better every day. But yeah, to answer your question, we're doing a mix of both. And as we've been developing expertise with the actual models.

• 15:08Craig S. Smith?

  Yeah. And can you give an example of how a law firm, for example?

• 15:18Craig S. Smith?

  Uh, or yeah, so let's say a law law firm that's handling uh compliance for a a bank.

• 15:26Speaker 00

  Yeah.

• 15:27Craig S. Smith?

  Uh, how they would use this.

• 15:30Speaker 00

  Yeah, so with a law firm, uh, the first issue, if they're a big law firm, is understanding what changes in regulation and legislation are relevant for which clients. So the first step is having abstract, you know, with its context of their clients, understand that, hey, this regulatory change is actually going to impact this bank, you know, banking industry type client, right? Once it identifies that, then it's a matter of calculating how it's going to impact that client, right? It may be an impact to their upcoming product that they're developing, or maybe an impact to their labor that they have in that state.

• 16:15Speaker 00

  So depending on the risk that arises, abstract's able to reason through and calculate like how that's going to impact the client. And then from there, that's where strategy sort of um takes place with respect to, you know, hiring a lobbyist or doing nothing and laying this turn to a compliance issue. Yeah. Why we'll note is that compliance is a reactive measure, and I can touch on this in a bit, but there there is a difference between compliance and being reactive and then sort of what we're focused on, which is more proactive side of of of the the space.

• 16:48Craig S. Smith?

  Yeah, uh, and who who are the main users? It's, uh, I mean, is it law firms? Is it lobbying firms? Is it, uh, uh, congressional staffers? Is it media? It sounds like a wonderful tool for media.

• 17:05Speaker 00

  Yeah, yeah, yeah. So really, the universe of of users is anyone that's trying to understand what the hell government's doing, right? Uh, which is a pretty big universe and only increasing. Um, however, right now, we're very much focused on large law firms and in-house legal teams within companies. Uh, and those legal teams usually work with government affairs or public policy. Those are dedicated, uh, you know, lobbyists and experts within a company, right, that work on that. So those are the two focus areas that we have is law firms and corporates. Um.

• 17:44Speaker 00

  Within that realm, uh, you know, it sort of varies who's working on trying to understand,

• 17:53Speaker 00

  trying to understand the government. Um, but usually we get pull from like the research people within these law firms or the business development units. Um, and then within the company, uh, usually the pull is, you know, whoever's ripping their hair apart about the tariffs that, you know, they're still trying to figure out or, you know, whatever it is that's, that's coming out that's going to impact the company. That's, that's our, that's our user typically.

• 18:19Craig S. Smith?

  Yeah. Does it also flag contradictions or in, uh, in, you know, across legislation? I mean, as you said, there's, it's a, it's a big universe of, of stuff. And that, that's one question. And, and do you, does it cover a global, I mean, for example, uh, you know, the AI Act in Europe or GDPR, does it cover changes? Because that's a whole nother animal.

• 18:53Speaker 00

  Yeah. So, uh, I mean, it's a good example, you know, over the last year, about 700 proposals, uh, were created, um, just on AI policy across the states. And that's because at the federal level, especially with this administration, there is very much this, you know, lack of appetite to do any sort of federal oversight on AI in, in the US. Um, whereas in Europe, this has become increasingly a priority to regulate at the EU level. Um, so touch on your first sort of question, uh, comparing these bills and seeing if there's contradictions is a very core piece of what we do.

• 19:36Speaker 00

  And it's, it's the reason why we have to ingest this data ourselves. It's why we're scraping and structuring all this noise ourselves. Um, so with that corpus of data, we can draw connections and ties, right? And, and maybe even see if there's contradictions. On the international, uh, sort of stage, it's very much top of mind. Um, you know, we're definitely focused right now on within the US, but we plan to, uh, expand internationally, um, soon thereafter.

• 20:09Speaker 00

  Yeah.

• 20:10Craig S. Smith?

  Um, and you you mentioned that there may someday be a consumer

• 20:18Craig S. Smith?

  platform. Uh, because that, I don't know. How many people are really interested, but it would be wonderful to be able to go to something uh authoritative uh and you know, ask what's being done on self-driving legislation, uh, you know, at the federal level and across the states. Uh, uh, and and it wouldn't uh that your platform would would pick up all of that, right? It it it adjusts only at the federal level, but at the state level.

• 20:56Speaker 00

  Yes, yeah, so the the vision raised, you know, across even local, right? Local, state and federal. Being able to abstract and distill what's relevant to the individual. And that should guide who you want to vote for.

• 21:11Craig S. Smith?

  Yep.

• 21:12Speaker 00

  You know, the the issue is that we we now vote based off of voter guides and whatever we're seeing on, you know, Facebook or friends are telling us, right? But ninety-nine percent of what you know, these elected officials do is what we're talking about is legislate, is create bills. Ninety-nine percent of the constituent body has no idea what these bills are.

• 21:35Craig S. Smith?

  That's true.

• 21:36Speaker 00

  So if we're able to make sense of and and you sort of break down the the impact that these bills have to the constituents. We should be a much more educated constituent body and therefore elected officials align more closely with what we actually believe in. So that is definitely, you know, sort of like the end goal, the end vision. And uh that same concept applies to business, you know, it's just different priorities.

• 22:02Craig S. Smith?

  Yeah, and you, when you were talking about uh uh government bodies, you you said all the way down to school districts. Does this cover the school district level across the country?

• 22:15Speaker 00

  Yes, so that's why uh there's a hundred and forty thousand plus uh governments in the US is because of all the special districts, uh cities and counties. Um so yeah, even your local school district has some sort of board. That board meets on a regular cadence and they're putting together um you know, sort of rules that they follow, right? Um and we're able to track that as well because they're all required by law to post this online. Um.

• 22:45Craig S. Smith?

  Well, wow, yeah. And and just cumul- cumulatively, it seems that that the burden of that data would grow exponentially. Uh

• 22:59Craig S. Smith?

  what what do you, do you archive data? I mean, as you update data with new information, uh do you archive the stuff that's being overwritten or or is this kind of a living snapshot uh that that moves through time?

• 23:19Speaker 00

  Yeah, it's definitely um a living snapshot, right? That lit moves through time, but we, you know, we have all the archives. So um I describe it very similar to like Git uh GitHub uh where you know, you have a piece of code and some people add some code and you know, that's a an addition, they delete it, you know, it's an amendment, it's deleted, it's, so we track all the changes and that's all archived. So nothing's lost. And there's insights there as well, right? If there was some, you know, uh tax policy that came out in California and that was amended over the years, seeing how it was amended,

• 23:58Speaker 00

  seeing who amended what, these are insights that are valuable. So this was, you know, very hard to do a decade ago. Um but funny enough, you know, I predict that the sort of corpus of data here is uh it's still much smaller than the foundational model companies and what they're doing. Um although it's non-trivial.

• 24:20Craig S. Smith?

  Yeah, and can you track? I mean, you were saying you can track amendments. Can you attract where certain amendments originated?

• 24:33Speaker 00

  Uh, yes, so amendments to policy come from

• 24:40Speaker 00

  the elected officials, right? As the bill goes through the legislative process, right? So if we have a bill that's introduced today, it has usually about 12 to 24 months to pass through all the committees, right? And then go through the other house, pass through those committees, be voted on unanimously, and then it turns to a bill signed by the governor or signed by the president at the federal level.

• 25:07Speaker 00

  When the amendments are proposed, that is posted, right? Publicly, so we do pick that up. And we know which committee amended a bill or who proposed an amendment.

• 25:17Craig S. Smith?

  Yep. Yeah.

• 25:22Craig S. Smith?

  I mean, it just comes to mind the the lowering of the excise tax on tanning salons, you know? But they got a lot of press and I've never seen the person identified who introduced that, but I would your system.

• 25:44Speaker 00

  We'll get closer.

• 25:46Craig S. Smith?

  Yep.

• 25:46Speaker 00

  Yeah, we'll get closer. The thing is that amendments sort of come from the lobbying process and the lobbying process,

• 25:57Speaker 00

  you know, has various aspects to it. Uh, so being very concrete here, you can have a lobbying firm, a contract lobbying firm, you know, testify or talk to the elected official about, hey, we need to change this, right? Because the client I represent wants this change. It's a very direct way of lobbying. There's also trade associations and nonprofits that, you know, bring together a group of. You know, companies and they lobby on behalf of those groups, right? They're purposefully sort of, uh, you know, trying to hide who's the the sponsor behind that, right? But you just see the trade association.

• 26:39Speaker 00

  On top of that, they're associations of associations, right? To further add distance between who's actually trying to propose the amendment. And the last piece, which I think is, you know, one of the hardest, but one most effective. And we saw this a lot with Uber, right? And the contractor, uh, sort of definition of the contractor, the gig workers, right? Which is using PR and marketing to sway the public to vote and, you know, send amendments to their legislators a certain way. Because at the end of the day, the elected official cares most about their constituents.

• 27:21Speaker 00

  So if their constituents are saying you need to vote a certain way, they're going to listen to them. So if you have the ability to sway the public vote, that's usually the most effective, but it's the hardest.

• 27:32Craig S. Smith?

  And and those, the platform, uh, you you said at the beginning that it it, uh, helps, uh, guide lobbyists of for the most effective ways to influence legislation. Does it come up with a plan? Like if you want to influence this clause, uh, these are the committees you should approach, or these are the the jurisdictions, uh, that you should run ads or something like that?

• 28:11Speaker 00

  Yeah, so that is what we sort of label as like the strategy aspect. It's the most nuanced piece. It's what, uh, you know, to the extent I can share, um, something that, uh, we're very much working on. And, um, we're very close to getting to a point where that is, you know, sort of exceeding the capabilities of any individual or team of strategists. And because that involves understanding the industry, the client, uh, the existing laws and codes, right? Right now, that involves law firms, lobbying firms, industry experts, right? But This is what we're able to now accomplish with AI and agents.

• 28:55Craig S. Smith?

  Yeah, I I mean, it's it's again, that that world is very complicated and right now it it rela relies on relationships, right? If you're if you're I have a niece who works in in Alzheimer's of research and lobbying and you know, they know which congressional staffers pay attention to that or which congressperson is likely to

• 29:33Craig S. Smith?

  you know, act on their behalf, but it's all through relationships. Uh, this would would make it more scientific, so to speak, right? In that you could, even if you didn't have a relationship, you could identify people who maybe you didn't know about or firms that you weren't aware of. Uh, is is is that right? Or?

• 29:58Speaker 00

  Correct.

• 29:59Craig S. Smith?

  Yeah.

• 30:00Speaker 00

  And even beyond that, um, not to get super technical, but uh, there is, we're just talking about the legislative process, right? What goes under the radar typically is the regulatory process. Um, that's sort of where the bill is implemented, the rules are applied and the the people that work in the regulatory agencies are, uh, you know, they're not elected. And that is a totally different process of, you know, you can't really influence them. Um, but you can get really granular and you know, almost get to a level of influence where.

• 30:42Speaker 00

  You know, the way that those officials are looking at the public comments for the regulatory agency are swayed one way or the other. But I believe that the personal relationships. So, you know, we're, that's not going to go anywhere far anytime soon. I mean, it's gonna be a while before we have AI legislators. I don't, that's a whole other topic. But I think what this sort of technology is bringing to the space is, to your point, making it much more calculated, more scientific, and as a result, it becomes more accessible and more transparent. So it should level the playing field in certain ways. So it's fascinating,

• 31:25Speaker 00

  sort of seeing it unfold in front of our eyes.

• 31:29Craig S. Smith?

  And how, how do you charge for this? Is this a subscription model or is it by seat?

• 31:37Speaker 00

  Or? Yeah. Yeah. So a lot of AI companies have had to redefine their approach to pricing because a lot of the value is more akin to what a team of people would do. So we actually do not

• 31:57Speaker 00

  charge off of seats. We charge off of coverage. The more government entities that we are abstracted for you, the more that we, we charge accordingly. But that's the value that we sort of see tied to the output for them.

• 32:12Craig S. Smith?

  Right, right. I see. So, yeah, you could have,

• 32:20Craig S. Smith?

  you know, down to the school district level, or you could just focus on the federal level or something like that. You would be charged differently. Is that right?

• 32:29Speaker 00

  Exactly. If I'm a, you know, big law firm and I'm trying to cover 20 more cities or regulatory agencies without abstract, I'd have to hire more people to cover those government entities. So that's why we charge off of coverage because the alternative would be hiring more headcount.

• 32:50Craig S. Smith?

  Yeah. Have you had any?

• 32:54Craig S. Smith?

  I mean, your job is not to affect legislators, to provide the tools, but have you have you had any?

• 33:03Craig S. Smith?

  Are there any examples of legislation that was impacted by? Uh, people using your platform? And by the information that was surfaced?

• 33:15Speaker 00

  Yeah, so like, um, you know, one example is a city in the state of California. That's one of our customers. And, you know, there's like a dam, right, that they were working on. Um, sort of getting, trying to get funding for it. Um, and so Abstract was able to identify that, you know, this is a relevant. A bill that, you know, if you were to amend a section of it. You will be able to, uh, obtain funding for the city. To fund this dam project, no pun intended, uh, literal dam for, uh, for the lake, right? So, um, that was an example, Abstract identified something that's relevant.

• 33:58Speaker 00

  Help them, you know, sort of provide an amendment to that bill. And the bill was able to be, uh, codified. And they're able to, you know, obtain that funding to to go forth. That's sort of a best case scenario for us.

• 34:13Craig S. Smith?

  Yeah, does the platform, uh, can it draft, uh, legislative language to propose?

• 34:21Speaker 00

  Yeah, so drafting is part of, um, sort of the generative AI aspect of what we do right now. Um, there's a couple of use cases in terms of, uh, generating content. And that we've been exploring includes that also includes like reports and whatnot. And, but the the short answer is yes, like that that's part of like the generation of content that we are creating around this.

• 34:46Craig S. Smith?

  Yeah, I mean. You can imagine, uh, that it could be really powerful in generating. Uh, lobbying campaigns across all of the various channels. I mean, does it do that where? You you identify a piece of legislation and some language that that is going to affect your company. You want it to change and. Abstract gives you a kind of a plan of attack.

• 35:17Craig S. Smith?

  And then it generates emails and legislative language to propose and, you know, web apps, ads and all kinds of things. Does it do that?

• 35:30Speaker 00

  Well, yeah, that's so when we talk about the strategy and the overarching, you know, next steps like that, what you're mentioning are all aspects of that, right? That that is a key focus. And it's what we're, you know, sort of fine tuning, developing with our current customers. So I can't speak too deeply about it as of today, as we're developing and keeping some of that under wraps. But I would say thematically, what you're hitting on is right on the nail.

• 35:59Craig S. Smith?

  Wow. Yeah, I mean, I would encourage you to open it up to the public because there is, you know, there's, there's a lot being written right now about

• 36:14Craig S. Smith?

  people using AI to generate false narratives or or deep take videos, sort of things to and how that's eroding democracy. But the other side that I've always imagined is that AI could be a tremendous

• 36:36Craig S. Smith?

  accelerator or or driver of participatory democracy where, you know, individuals or or communities could use a tool like this to see how

• 36:53Craig S. Smith?

  you know, different proposals at different levels of government are going to affect them. I know in in my town, there's this perennial proposal to, you know, rebuild the downtown and and you, you know,

• 37:15Craig S. Smith?

  it'd be a full time job to keep track of what's going on there. It's like every few weeks. You read something but and you feel a little out of the loop. But if if you have a tool like this, you you could. Uh, check it uh daily or or or another question, does does this give alerts? If you follow a particular

• 37:39Speaker 00

  Yeah.

• 37:39Craig S. Smith?

  Of uh subject, would it would it uh alert you that something's changing that you should pay attention to?

• 37:47Speaker 00

  In real time, yes, that is a core core part. So, you know, you're looking at this downtown rebuild. You know, if the city council met and they uh I don't know, decided, hey, we're actually gonna kill the planner, the planters, and we're gonna do trees instead, right? You get an alert saying, hey, I know you care about this because I have context on the fact that you live here. And they just said that they're gonna introduce trees.

• 38:17Speaker 00

  Do you wanna reach out? Maybe, you know, maybe you want the flowers back. Um, but that's a really good example of um sort of how it would alert you and um do that based off of context of, you know, one knows about you.

• 38:31Craig S. Smith?

  Yeah, and and uh is is this prohibitively expensive? I mean, your your core market of, as you were saying, are really a large uh corporations and law firms. Uh, could it be made uh available at a at a price that that individuals or communities could afford?

• 38:55Speaker 00

  Yeah, so that's, I mean, this is why we're starting here and then expanding, you know, outwards towards the consumer. It is very expensive, right? Especially now in the earlier phases of of AI. Um, is why we're in enterprise-grade software. Uh, it's very bespoke, very custom, white glove solution.

• 39:15Speaker 00

  But as I said, you know, I I really, I see this as an investment to make this more accessible for the masses. And I don't think we're that far off. I think in the next five to 10 years, it's gonna happen. Um, and it's like with any technology, right? You look at, you know, it's overplayed example, but Tesla didn't start with everyday car. They started with the premium cars and sort of got things right before they were able to make that available to the masses.

• 39:40Craig S. Smith?

  Yeah, and what's your view of democracies that you're looking at this closely? Because

• 39:47Speaker 00

  Yeah.

• 39:48Craig S. Smith?

  I'm a great believer in the strength of America's democratic institutions, but there's a lot of concern. There's a lot of concern, as I said, about this information.

• 40:02Craig S. Smith?

  But for years now, I've talked to people about how AI could knit together the populace and sort of take a real time measure of their opinion.

• 40:22Craig S. Smith?

  And that that could be really powerful for democracy. So do you do you think

• 40:30Craig S. Smith?

  the tools like this are going to shore up democracy? I mean, I spent a lot of my life in China and there's a concern both among some Chinese, but certainly among people outside China, that the AI surveillance will be used to lock down dissent and reinforce the Communist Party. So it can be used against democracy. But yeah, I'm just curious, since you are in this space, what do you think?

• 41:11Speaker 00

  I think that a lot of what we see now is a result of companies.

• 41:20Speaker 00

  You know, I'll be very, you know, clear, like companies like Meta, right? Where their sort of North Star was retention and eyeballs, right? And that's the North Star that.

• 41:32Speaker 00

  Can be taken in directions that are not productive for society, right? And sort of focus on amplifying content that attracts eyeballs, but maybe not for the right reasons, right? And so, you know, I think a lot of sort of where we're at right now is a result of this increase of what I call noise and silos of noise that are, you know, very much catered towards communities, you know, based off what they care about. And the original intent was to create audiences, you know, for Meta, for Google and whatnot, to serve advertisements and monetize upon.

• 42:16Speaker 00

  But, you know, as a lot of us now know, that same technology is what led to a lot of these silos, which created, you know, at the worst end extremist groups, right? And, and so I think in order to,

• 42:34Speaker 00

  you know, from an optimistic perspective, see like where things are going. I think this is now a main concern across most executives at companies, across most of the government officials as well. And I think the fundamental fabric of American democracy is still built on the constituents, us people, right? And I think that the people that we elect, the elected officials, they succeed or die based off of our, our vote, right? And so I think what's going to happen is there's going to be a greater sort of like shift in people trying to figure out what are the elected officials doing? And, and that's going to be amplified through all these channels.

• 43:18Speaker 00

  So I have an optimistic viewpoint where I think AI is going to help us bring more accessibility and sort of more factual updates on what the officials are doing. But we're going to get a lot more, you know, fake data and fake, you know, news around that as well.

• 43:39Speaker 00

  So I know that was a roundabout way of saying there's hope, but it's going to be a nuanced and complicated road ahead.

• 43:46Craig S. Smith?

  Yeah, and that the fake data or disinformation, how do you guard against that slipping into your?

• 43:55Speaker 00

  Great question. So we don't have much of that issue on our end because our data by nature is all official. It's all facts, right? It's the official documents that governments are outputting. The only sort of areas where there can be fake data is maybe in the analyses or the strategy and documents that App check creates. But this is all worked on by professionals, right? I think we're one of the areas where fake data becomes problematic is when it's used to sway the public a certain way.

• 44:32Speaker 00

  You know, especially when it's not factual. So that's, that's my read of the scenario.

• 44:40Craig S. Smith?

  Yeah. Do you work with news organizations?

• 44:45Speaker 00

  So we have, I can't disclose here, but we have, yeah, we're working on partnerships with news like organizations. We're actually in that process right now. I think news and social media is a critical component now to understand

• 45:03Speaker 00

  the pulse of government, also because a lot of your local state officials and federal, they're tweeting and they're putting things on LinkedIn. Right? And so you may want to know about that tweet because they're talking about their next bill that they're going to change. Right? So it's a critical component.

• 45:22Craig S. Smith?

  Yeah. And I'm just thinking it would be, you know, amazing if you partnered with a news organization. They had a website that, that just gave this kind of analysis of, of, for example, the big beautiful bill or, or anything that up. So, uh, because you're right, democracy and America rests on.

• 45:51Craig S. Smith?

  People, but the people are grossly uninformed or misinformed in many cases. Uh, and you know, that's the breeding ground for populism. Uh, but if you, if people could actually see what's being done, understand that uh, it would be a much healthier constituency.

• 46:15Speaker 00

  I, I agree more. I think that's a, I'm gonna note that down. Um, I think that's a fair, yeah.

• 46:20Craig S. Smith?

  Uh. Yeah.

• 46:22Speaker 00

  Could, could be a good, uh, sort of free marketing for us too, right? While, while doing some good. I like this. I like this.

• 46:29Craig S. Smith?

  Where do people find you? Uh, is there any sort of a freemium, uh,

• 46:37Craig S. Smith?

  uh, layer that allows people to look at the product before signing up? Uh, is it self-service SaaS or is it, uh, uh, do you have to engage with a salesperson?

• 46:50Speaker 00

  Uh, all of that. Yeah. So long story made short, um, you can just Google my name, Patrick or Pat Oats. Um, I'm actually Argentinian, so some parts of the internet will say Patricio. If you're bold enough to type that in, but, um, just Google me and you can find my, my LinkedIn and information. Uh, but everything about abstract is at abstract.us. You can also just Google abstract US. Um, the way that we operate, again, given it's enterprise and white glove is, um, we have all the information on the website, but we essentially walk through a sort of intake process and scope everything out if people want to learn more.