# Invisible builds custom AI applications instead of selling more SaaS

Markdown copy of https://realalpha.app/s/invisible-builds-custom-ai-applications-instead-of-selling/ on Real Alpha, the best minutes from long interviews with the people building AI. Cite and link the page, not this copy.

- Speaker: [Francis Pedraza](https://realalpha.app/people/francis-pedraza/) · Invisible
- Host: [John Coogan](https://realalpha.app/people/john-coogan/) · Co-host, TBPN · Co-founded Soylent and Lucy; OpenAI bought his show TBPN in April 2026.
- Host: [Jordi Hays](https://realalpha.app/people/jordi-hays/) · Co-host, TBPN · Founded Branded Native; co-founded fintech Capital, which Rho bought.
- Show: TBPN
- Episode: [Thursday, September 25th](https://realalpha.app/v/QL_GSxeXG5I/), Sep 26, 2025
- Moment: 2:47:10 to 2:54:22 of the episode (7 min), playing on https://realalpha.app/s/invisible-builds-custom-ai-applications-instead-of-selling/; the episode from there: https://realalpha.app/v/QL_GSxeXG5I/?t=10030

## Quote

> “They will sell them **tools to make a cake**, and the customer then has to hire a systems integrator like Accenture”
> — [Francis Pedraza](https://realalpha.app/people/francis-pedraza/) at [2:47:32](https://realalpha.app/v/QL_GSxeXG5I/?t=10052) · TBPN

## Takeaways

1. Enterprises often need integrators to connect separate SaaS products.
2. Invisible pairs a horizontal platform with field engineers.
3. Custom solutions can turn an initial services effort into durable revenue.

## About this segment

Francis Pedraza says enterprises often buy SaaS tools, then pay integrators to connect them into working solutions. Invisible combines a platform with embedded engineers to build custom AI applications that can become durable software revenue.

From “Thursday, September 25th”, Sep 26, 2025. [Watch the full episode](https://realalpha.app/v/QL_GSxeXG5I/)

## Transcript

From the transcript TBPN publishes with the episode.

[2:47:22](https://realalpha.app/v/QL_GSxeXG5I/?t=10042) So ten years ago when we founded the company, there was a question, which is if there's an app for everything, why isn't everything perfect yet? And Salesforce was the first SaaS company in 1999. For the last twenty five years, every enterprise software company has been a SaaS company. Mhmm. And this has actually put customers in a pretty absurd situation where if the customer wants a cake, Silicon Valley will not sell them a cake.

[2:47:45](https://realalpha.app/v/QL_GSxeXG5I/?t=10065) They will sell them tools to make a cake, and the customer then has to hire a systems integrator like Accenture to stitch together all these SaaS applications into an end to end solution that actually works for the business. And so, that is what we were disrupting. And Palantir was not public yet, so they weren't a well understood comp. We were kind of like an ugly duckling because we were talking about AI services. Mhmm.

[2:48:08](https://realalpha.app/v/QL_GSxeXG5I/?t=10088) And, and so it's just a fundamentally disruptive business model. So you were you were competing initially with someone like an Accenture to integrate existing software systems. Is that right?

[2:48:19](https://realalpha.app/v/QL_GSxeXG5I/?t=10099) Yeah. We build custom AI applications for enterprises and governments. And so you can think of this very different than SaaS, like a triangle. We have the horizontal platform, which is very powerful, but you have field engineers and field CTOs and a forward deployed motion that builds custom AI applications that actually solve the problem for the enterprise and the government. And our insight was that even though every, you know, solution would be custom, the horizontal platform would allow you to sort of build infinitely customizable software over time.

[2:48:47](https://realalpha.app/v/QL_GSxeXG5I/?t=10127) That makes sense. We've been seeing Mark Benioff and Doctor Karp, going at it over various contracts, Salesforce, which you already mentioned, Palantir, which you mentioned. Yeah. Are are you are you in that knockout, drag out fight? Have you found a differentiator around industry or size of problem, or or are you just going in the the arena?

[2:49:12](https://realalpha.app/v/QL_GSxeXG5I/?t=10152) So Salesforce was founded in 1999. Palantir was founded in 02/2003, so way before the Gen AI era. So we were in a sense like the Gen AI native, way of doing this. We hired Matt Fitzpatrick who previously ran McKinsey's Quantum Black Labs, and, he's now our CEO. And, after years of being capital efficient, this round sort of enables us to go into a pre IPO motion. And, yeah, if you're a public markets investor, you don't really have that many options for buying AI today. Mhmm. So and this is generally true for the enterprises, the customers themselves. If you wanna build custom AI, you know, solutions, Palantir is like a data integration and decision making support company. Mhmm.

[2:49:51](https://realalpha.app/v/QL_GSxeXG5I/?t=10191) So they really they really focus on that. But if you have a problem in anywhere else in your business, how do you build a custom, you know, solution with world class field engineers? It's a very different type of engineer, very different type of go to market person, very different type of business that is familiar building custom solutions on the enterprise. You know, enterprises do not want their data to leave their systems. So they they need their they need all the solutions to be on prem and containerized, we have the ability to build, in that way.

[2:50:23](https://realalpha.app/v/QL_GSxeXG5I/?t=10223) Do you find do do you think that there's a shift in the AI era to large enterprises doing more of these sort of, like, semi custom solutions? Is that's gonna be a continuing trend? Because it feels like the last era was very much, like, rip out the old custom on prem solutions and go to some sort of, like, one size fits all cloud solution.

[2:50:48](https://realalpha.app/v/QL_GSxeXG5I/?t=10248) Exactly. Yes. And this is a reversal. We're going all the way the other way. And I think that's because enterprises ultimately need proprietary and custom solutions. So they in the SaaS era, like I said, they were stitching together things, and they had to do that with some combination of, like, their internal engineering function and systems integrators. And systems integrators are not tech companies. They're gonna overcharge, under deliver. You're gonna pay them by the hour, so their incentive is to bill you as many hours as possible without getting fired, and that's not really aligned with efficiency. And so in in this era, I think, you know, enterprises are realizing it's gonna be very, very difficult for them to build world class engineering teams and to build a platform like the one we have, where, we can take the best models, latest models, which we train.

[2:51:31](https://realalpha.app/v/QL_GSxeXG5I/?t=10291) We have an AI training business, and deploy them in the enterprise, to actually solve the business use cases that they that they have.

[2:51:40](https://realalpha.app/v/QL_GSxeXG5I/?t=10300) Yeah. So so how much should we read into you guys transitioning away from training? Is that a business that is

[2:51:47](https://realalpha.app/v/QL_GSxeXG5I/?t=10307) We're not transitioning away. We are fully committed to training. So actually, the the move of Meta acquiring scale basically cleared the field. And so it's an it's inherently oligopolistic market structure where there are a few players that have invested as much as we've invested over as many years as we've invested. And so we have, like, 20,000 experts, and that number is scaling very quickly. We can hire, like, a thousand experts a week. So when you're asking a model a question about, the chemical properties of silver or the the history of Sweden or whatever you're asking a model, we have PhDs, masters, experts in every subject that are training these models and there's, you know, evals and and and lots of, you know, inputs into making these models great.

[2:52:31](https://realalpha.app/v/QL_GSxeXG5I/?t=10351) Got it. So leveraging the experience on the training side in order to help the To deploy the enterprise. Got it. Got it. Exactly. And then what Yeah. And and then and then the the business model for for the deployment side is I'm just gonna repeat it back to you so I so I understand is there's some period that looks more like services, but it becomes a piece of durable software that they can use for a long It's great model.

[2:52:57](https://realalpha.app/v/QL_GSxeXG5I/?t=10377) Long Exactly. Yes. Yeah. Yes. Got it. Cool. AI AI services is, exactly that way. Yeah. What yeah. And that that puts us in an investing mode. We literally invest in our customers. So Mhmm. We put, you know, field engineers, field CTOs in with our clients, and there's an investment period to build the solution. But once the solution's in place, that is very durable revenue.

[2:53:18](https://realalpha.app/v/QL_GSxeXG5I/?t=10398) And so you're you're like a nightmare for someone like an Accenture, some of these big consulting companies that don't really have the true expertise around training these models and you get to and and have a lot of organizational bloat. Is that is that right?

[2:53:34](https://realalpha.app/v/QL_GSxeXG5I/?t=10414) Yes. So, Matt, who, Matt, who's our new CEO, we bonded over ancient Greek and Roman history, and he calls it the battle of Thermopylae because even if you even Accenture has, like, a million people worldwide and has some huge headcount. If there's three if the pass is only yay wide and there's 300 people at the pass and we're always winning at the pass, then we're gonna win every battle. In other words, if you know, I believe our technology is superior dramatically superior already to traditional systems integrators. So if you're a buyer and you're hearing Accenture's pitch and Invisible's pitch, which one are you gonna pick?

[2:54:09](https://realalpha.app/v/QL_GSxeXG5I/?t=10449) The battle of Thermopylae, Spartans win.