Building a Venture Scale Enterprise AI Company from Spain: David Villalon, CEO of Maisa (Part 6)

Sramana Mitra: What I like about your pricing model is that it aligns with the ongoing debate between subscription, value-based, and usage-based pricing. Subscription pricing remains the most attractive model in our industry. If you can make it work without breaking your unit economics, it’s the most desirable for everyone — enterprises, buyers, startups, and even analysts.

From a financial perspective, subscription businesses are easier to evaluate, whether you’re raising money, going public, or getting acquired. So, what is your financing strategy? Is this bootstrapped, or have you raised money?

David Villalon: Great question. We first raised $5 million from NFX and Village Global, two VCs from the Bay Area.

Sramana Mitra: When was that?

David Villalon: Around December 2024. We actually closed it a few months earlier but announced it then.

Sramana Mitra: What did you have in the company at that point?

David Villalon: We had our KPU technology, strong ideas, and a solid team. We also had proof of early customer interest — two potential customers, one of which has since converted.

Sramana Mitra: That’s not really a pre-seed; that’s much further along. You can call ot a pre-seed if you want to, but it’s not a pre-seed by any stretch of imagination. Anyway, you raised $5 million — and then what?

David Villalon: Things have been moving fast. We recently closed a $25 million seed round, which should be announced next week.

Sramana Mitra: $25 million is not seed; it’s more like a Series A.  You’re using these random names, but those are not correct.

David Villalon: You will see in crunch base in everywhere that it’s 25 million seed.

Sramana Mitra: You can call it that, but that’s not what it is.

David Villalon: It is. I believe we do have product-market fit.

Sramana Mitra: You’ve over $5 million in revenue. That’s not a seed stage.

David Villalon: I think it is. I believe we’re just 10% of what we’ve to do.

Sramana Mitra: That’s not the point. That’s not how pre-seed and seed are designed. You can call it whatever you want, but you’ve to understand how the industry works a little bit as well.  The industry doesn’t call a company with $5 million revenue as a seed company. That company has already found product-market fit. You’ve already found product-market fit.

David Villalon: I have seen companies doing more in less time

and then going down. It may be that the market moves really fast. The

dynamics of the market are changing very fast.

Sramana Mitra: That’s a different point. Yes, and what I love about your story is that you have real use cases in production. Many AI startups get stuck at the proof-of-concept stage and never reach production. Your use cases are live, you’re getting repeat business, and you’ve built a portfolio of about 15 enterprise customers where you can land and expand into production. That’s fantastic — exactly what enterprise AI companies are aiming for right now.

Now, I have one question apropos your deployment model. You mentioned a fee for getting a company to its first production use case and referred to “services.” Do you have to provide services to get customers up and running?

David Villalon: We don’t have to, but we want to. Not because of the money, but to ensure success. If the use case is something like invoices, we might not charge at all unless it’s complex and requires several weeks of our team’s time.

Our platform is unique, and onboarding is like teaching someone to ride a bike — we guide them until they can go on their own. We want you to win. We’re happy when the customer is happy. We assign an automation engineer to help customers through their first use case. The goal is not to do it for them but to help them learn and gain confidence.

The rationale behind this is that we want to create momentum. If there’s no one internally who understands how the platform works,

Sramana Mitra: You want to have internal champions to drive further adoption.

David Villalon: So, it’s not about making money from services; it’s about ensuring customer success.

Sramana Mitra: Exactly — and helping them understand enough to identify the next ten use cases they can automate. Your team won’t know those use cases; the enterprise will know what those use cases are.

David Villalon: Exactly. That’s what happens with us all the time.

Sramana Mitra: Fantastic. What else would you like to share? How big is your team?

David Villalon: We’re 33 people today, growing to around 40 in a couple of weeks. By the end of the year, we expect to be about 55 to 60.

Sramana Mitra: Where is your team based geographically?

David Villalon: About 90–95% are in Europe.

Sramana Mitra: Not only in Valencia, but different part of Europe.

David Villalon: Yes, not only in Valencia but also in Switzerland, London, Germany, and Spain. We also have a few people in the U.S., mainly in sales and go-to-market roles. About 90% of the core engineering and AI teams are in Valencia. I’m in the office now, though we’re remote-first and only meet in person once or twice a week. I prefer that people don’t have to come to office every day unless they want to.

Sramana Mitra: And of your 15 enterprise customers, how many are European?

David Villalon: 12.

This segment is part 6 in the series : Building a Venture Scale Enterprise AI Company from Spain: David Villalon, CEO of Maisa
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