Trunk Tools Launch: Disrupting the $15 Trillion Construction Industry with Autonomous Agents

Talk transcript

1. 0:00

   [on-hold electronic music]

2. 0:13

   Welcome, everybody, to this little afternoon session of mine. I'll keep it very short, but this is gonna be the most exciting presentation of the day because I'm talking to you about construction. [audience cheering]

3. 0:23

   Thank you. Um, we are Trunk Tools. Trunk Tools is the leading generative AI provider for the construction industry, which probably none of you have ever thought about it, but you are consuming construction every single day.

4. 0:34

   You're sitting in it right now. You're driving in, in it on your day home, uh, on your ride home, and it is the most exciting industry in the world.

5. 0:42

   Um, I'm gonna level set the stage here a little bit. This is a building that is, um, being built in New York City right now, and it's using our software.

6. 0:50

   We asked this building to give us access to all their documentation, okay? Raise your hand if you think they gave us access to more than 1,000 pages. Come on, don't be shy.

7. 0:58

   This is not an engineering conference. Keep your hand up if you think it's more than 10,000 pages of documentation, 100,000 pages of documentation, a million pages of documentation to build a single skyscraper.

8. 1:09

   They gave us access to a total of 3.6 million pages of contract, okay? 3.6 million pages of pictures and blueprints and schedules and RFIs and all of this stuff.

9. 1:23

   If you were to print that, a stack of paper three times as high as the building itself. [audience laughs]

10. 1:29

    That's why I'm super excited about this industry, and that's why this industry is literally built for RAG. That's why they put me up on this RAG stage here. Why do we have such a problem in construction doing this?

11. 1:40

    There is massive amounts of people making decisions every single day, and they're documenting the heck out of this because it's one of the most litigious industry that you w- that you will ever see.

12. 1:49

    Similar to software development, right? Like, we-- I have a PhD in AI and construction, so I kinda know what I'm talking about, but I'm not an expert. That's why we have better people on my team.

13. 1:56

    But similar to software developer, right, you have lots of people writing code, but once you merge it together, it actually breaks, and you have bugs. In construction, that happens once you are in the field, and you're trying to pour the concrete, or you're trying to squeeze a pipe into a hole, and it just doesn't fit.

14. 2:11

    Construction is $15 trillion a year, trillion with a T. 10% of it is rework. 10% is because there's data discrepancies in this pile of data that the people don't know about it, 1.5 trillion US dollars every single year, and that's what we are solving.

15. 2:27

    We are putting all of this knowledge in one place, which is what we call the brain behind construction, obviously a RAG product, that goes in, perfectly digests and memorizes all of these construction-specific file types.

16. 2:40

    Yes, we built RAG specifically for a vertical. This vertical, however, is 10% of GDP. Once we have built this, we are deploying on top of this brain an army of AI-based agents.

17. 2:53

    Agents are more or less intelligent, and we can dive into this if you come to our booth a little bit later. I show you one of these agents live in practice in the field, okay?

18. 3:01

    This is a traditional copilot. You have all seen this a million times. You ask a question about your 3.6 million pages of construction data. Within a few seconds, you get an answer, and you obviously also want the source to the original file document.

19. 3:14

    Used on billions of the construction volume right now, I'm showing you an example from an actual construction site. Does door number 2,103, number two, needs power actuated hardware? Yes, a very important question on a construction site.

20. 3:30

    The way this works for us, you throw this question against the system via text message or via web app. Within a few seconds, we give you the enterprise search results, and obviously, we also give you a semantic answer to your actual question.

21. 3:41

    Interestingly enough, for anybody who actually wants to read what's up there, there is discrepancies in the answer. The answer itself shows that in the 3.6 million pages of documentation, actually somebody made a mistake, and that mistake is gonna be very, very expensive.

22. 3:55

    To give you a sense of the unstructured mess of data we are dealing with in construction, let me open one of these files.

23. 4:03

    Beautiful. That's how we structure documentation in construction. Three-feet-wide tables with a ton of numbers, unusable for any human. That's why we're throwing AI against it. Obviously, I was talking about data discrepancies.

24. 4:16

    Instead of stopping where we have the data discrepancies, why don't you use an agent that is just actually creating an RFI and solving the discrepancy for the human so that the human can go back doing their job and not being a victim of bureaucracy?

25. 4:30

    I'm on a RAG stage, but personally, I believe that RAG is completely commoditized. So what am I doing here? I'm here to tell you for whoever is building RAG that the future of RAG is actually keeping the human in the center and augmenting the human with an army of agents that is solving real-life problems.

26. 4:49

    Because if you actually wanna have an impact in the real life, then in my opinion, vertical agents solving real-world problems are the future. If you're interested in joining us on that path and being in the sexiest industry in the world, come join us at our booth in the expo hall.

27. 5:04

    We're called Trunk Tools. Here's a QR code. We are hiring left and right, and we're very excited to be dominating one of the most impactful industries in the world.

28. 5:11

    Thank you. [audience applauding] [on-hold electronic music]