He Raised $185 Million To Build An Open-Source Data Integration Platform To Move Data From Various Sources Into Data Warehouses, Data Lakes, And Databases
Some founders dream of billion-dollar outcomes. Others quietly stack experiences, industry by industry and skill by skill, until their time arrives. Michel Tricot is the latter.
Before co-founding Airbyte and raising $185M, Michel helped build two companies that sold for $300M and $115M, respectively. Yet, his story isn’t about overnight success. It's about relentless curiosity, global perspective, and a deep belief that data should move as freely as ideas.
Michel’s path from the Swiss mountains to Silicon Valley, from harvesting tobacco to architecting a petabyte-scale system, shows that true entrepreneurs aren't born; they’re forged through grit, learning, and the refusal to ignore an itch to build.
Early Roots: Mountains, Movement, and Machines
Michel was born in Switzerland, a childhood painted with alpine slopes and early mornings on skis. Frequent moves from Switzerland to Strasbourg to Paris shaped more than geography.
As he recalls, “When you move a lot, you get less attached to places and more to the people around you. It tightens your bond with family.”
Tech didn’t enter through a classroom. It entered through obsession. A family friend had a room full of computers where Michel dove into Prince of Persia, Tetris, and hacking experiments long before he owned a machine himself. He did his middle school in France.
To buy his first computer, a second-hand device, Michel worked summers on farms, harvesting tobacco. This wasn’t a kid dabbling in programming. It was someone building a foundation for a lifelong craft.
When faced with the choice between studying medicine or computer science, the decision was clear: Silicon-based machinery over human machinery. And, it paid off.
Princeton, Brain Imaging, and the First Taste of America
While studying engineering in France, Michel earned a six-month internship through Siemens in partnership with Princeton. Here, he worked with a researcher on cutting-edge computer vision for brain segmentation. He wasn’t just coding; he was helping improve surgical decision-making.
As Michel says, “It could detect disease in the brain from specific modalities. That was a very fun moment.” The product was designed for sale to hospitals and helped map the different areas of the brain by their functions.
Landing in New York for the first time and experiencing the towering architecture, wide roads, and neon energy lit the spark. The American dream wasn't a slogan. It was a destination. Visa challenges briefly sent him back to Europe, but instead of doors closing, a new one opened: FactSet.
There, Michel entered the world that would ultimately define his entrepreneurial destiny--data at scale. “That’s where I learned what it means to collect data at scale, prepare it, and make it actionable for the end user,” he remembers.
At the time, Michel was shuttling between New York and Paris, and his work focused on data for traders and quantitative analysis.
Silicon Valley Calling: Moving to San Francisco and Joining LiveRamp
Michel was keen to return to San Francisco and the Bay Area in the US. His reasoning was that it was where tech was happening and where talent was headed. Thus, on December 31, 2010, he and his fiancée made a life-shifting decision: Move to San Francisco.
The duo was determined to change something in their lives. Michel remembers calling a few of his college mates with whom he had worked on a school project. One of them had joined Rapleaf (then LiveRamp). That’s where Michel decided to go.
Three suitcases. No guarantees. A vision. That’s what he and his fiancée had.
In 2011, Michel joined LiveRamp as one of the first 25-30 employees. They had an initial, reactive product, but had started to pivot into the ad tech space. Soon, they began moving data between different advertising platforms to target online users better.
As Michel explains, they weren’t doing anything advertising-related; they were simply moving pieces of information so that online advertising was customized for the audience that consumed it. They were actually processing petabytes worth of data.
At the intersection of exploding mobile adoption and a new ad-supported internet model, Michel learned what hypergrowth really means. He progressed from manufacturing data to managing large-scale data with the assistance of a small team.
The $300M Exit and Valuable Lessons Learned
Michel quickly realized, “Small teams of driven people can do wonders. LiveRamp made bets on young talent and let us do ambitious things.” He saw three fundamental truths:
Timing matters: The right place at the right moment in the mobile and internet boom. People were leveraging this new business model, which offered free content. However, users had to watch some ads, and LiveRamp provided the ad display. · Talent compounds: Motivated builders reshape markets. Humans can make the ultimate difference in the company they’re building and accomplish marvelous things if they can understand where the company is going. · Bet on people early: Great companies aren’t staffed; they are cultivated. LiveRamp made the strategic decision to hire lots of young people and give them the chance to take on ambitious projects. The company excelled at managing teams and organizations.
LiveRamp was later sold to Acxiom for $310M, and alumni went on to build dozens of companies. Michel took notes.
rideOS, $115M Exit, and World Tour in Startup Training
After LiveRamp, Michel planned to start his own company, but opportunity knocked again. A former Uber team launching rideOS invited him to join. Self-driving tech was emerging, and big automakers were listening. The company signed major deals with key US car manufacturers.
However, six months in, Michel told the CEO that his founder journey was still ongoing. Instead of pushing back, the CEO accelerated his growth. He suggested that he and Michel work together so Michel could build on the skills he had gained at LiveRamp.
The CEO took him on global partnership tours to China, Japan, Germany, and France, among other countries. · Taught him high-stakes fundraising · Gave Michel exposure beyond engineering
“I hit every wall possible. That’s how you learn,” Michel recalls. rideOS was later sold for $115M. He had the one final piece of the puzzle: a hands-on CEO apprenticeship. It was time.
Side-by-side, Michel continued to work on the technical aspect--making data actionable for end users. He also continued to grab every opportunity to learn outside his comfort zone and domain of experience. He had taken away great lessons from the acquisition and was ready to apply them.
Enter Airbyte: The Data Movement Revolution
In July 2019, after a decade of building at the frontier of data systems, Michel finally hit “go.” He gave himself a month to reset, then spent months brainstorming and validating ideas, many of which were outside his expertise. He brought in team members from LiveRamp and his now co-founder.
Lesson learned? “Only explore markets you deeply understand. Don’t waste cycles elsewhere,” Michel says. By January 2020, Airbyte was incorporated and accepted into YC. Then COVID hit. Everyone was home. Everyone needed better data movement.
As Michel explains, they created what they called a data movement platform, which enabled them to connect to any systems, extract data from them, and make it available to downstream systems. Their end goal: to make data universally available.
The platform would pull data from systems and send it to places where it could deliver value. Initially, Michel and his team focused primarily on analytics and loading data into data warehouses.
Over the past year and a half, they have also been involved in bringing more data and building context for agentic systems. Most importantly, the platform is open source, which means it has a large community of users who are both users and contributors to the project.
Leveraging COVID and Zoom Calls to Understand Pain Points
Initially, Michel spent a lot of time on user discovery, and here, COVID became a blessing. People were bored at home, leading to increased activity on LinkedIn. Everyone was trying to connect with specific roles and titles on the platform.
At the time, Michel and his team were targeting data engineers, directors, and other professionals with similar profiles. They organized 200 to 250 Zoom calls over the course of a few months, spending 15 to 30 minutes on each, just trying to understand their day-to-day pain points.
Michel and his team took notes on Google Drive, creating courses as they went along, narrowing the information down according to their objectives. That’s a strategy they maintain to this date and have integrated it into the Airbyte culture.
Michel and his team connected with the community, asking users about their pain points and the “magic wand solution” that can solve those problems. Next, they incorporated the feedback into the product.
However, as the open-source project completely took off, Michel encountered a new challenge. He had a highly efficient but small team, which was quickly getting swamped by all the community interaction.
Raising the Series B Funding Round to Scale Airbyte
Although community engagement was a positive sign, it also meant that the team was spending too much time on the community and not enough on building the product. It was now time to scale the company. To do that, Michel needed to raise their Series B funding round.
The signals were strong and the time was right, even though the product was still immature. However, as Michel realized, people were going above and beyond to make it work for their use case. The pain points that Airbyte solved were so acute that anything was better than what they were doing.
Open-source traction. · Users love the idea. · They install, hack, and contribute. · But monetization is not yet defined.
A clear, urgent pain. · Users tolerate imperfections because value is non-negotiable. · Revenue follows pull, not push.
At this point, monetization becomes a different story because user expectations are changing. Founders need to be very intentional about the use case they want to serve. In open source, they don’t know how people are using their products.
Michel had initially built Airbyte to enable users to put more data into warehouses. But some people were using it for cache hydration or for additional use cases that did not align with Airbyte’s monetization roadmap.
The Transition: From Project-Market Fit to Product-Market Fit
Michel’s solution was to narrow down the number of use cases. However, they also built more support to deliver the exact value that users wanted. Their killer unlock? Data sovereignty.
In an AI era, control and privacy aren’t features; they're religion. Michel told users, “We can connect to every single system, but we can also connect to the most sensitive system that you might have, and you will never have to share any information with a third party about the data you're moving.”
People could just move their data, access a simple platform, and remove all the pain of building all these different pipelines. That was the main use case for why people were using Airbyte OpenSource. Demand skyrocketed, prompting fundraising.
In retrospect, Michel points out that if you’re wondering whether you have product-market fit, you likely don’t. In the early stages of building the product, accept that it will have deficiencies. Focusing on creating a perfect product will delay the launch.
However, you have a win if customers accept that pieces are missing and are willing to work around them--simply because it addresses an acute pain point. Users are open to a product that will improve and evolve over the next year or two. It’s as though the customer is fuelling the energy.
Raising $185M: Discipline Over Dollars
Michel raised almost all rounds within a year, including seed, Series A, and Series B. Overall, the business was very similar to what it had been a few months ago. This made the process a lot simpler.
Storytelling is everything that Michel Tricot was able to master. The key is capturing the essence of what you are doing in 15 to 20 slides. For a winning deck, take a look at the pitch deck template created by Peter Thiel, Silicon Valley legend (see it here), where the most critical slides are highlighted.
Remember to unlock the pitch deck template that founders worldwide are using to raise millions below.
The challenge wasn't securing capital. It was not losing discipline. “Just because you have money doesn't mean you spend it. You earn the right to scale,” Michel says. His playbook:
Create experimentation hygiene · Commit only when the experimentation is validated · Choose investors who understand open source · Protect long-term user base before monetizing aggressively
As Michel explains, project-market fit involves building a large user base that deploys the platform to move data around. However, this strategy also entails creating a substantial user base, as just 10% to 20% of users are likely to become paying customers.
Michel points out that open source is costly in terms of time and product development. They also needed to convince investors about the potential for returns. At the same time, open source isn’t just a business model; it’s a community flywheel. Michel embraced it.
The Data Future Michel Is Building and Lessons Learned
Airbyte’s endgame? A world where AI agents autonomously discover, extract, and leverage data across an organization, without endless manual wrangling. “Accessing data should be a no-brainer. I want intelligent agents deciding what data to move and integrate into their processing.”
In other words, turning every company into a data-driven machine, without the need for armies of engineers to manage and integrate data.
Asked about lessons he would give to his younger self, Michel says, “Don’t explore markets you don’t understand. Stay where you have depth.” And for founders:
Let users write your roadmap · Depth > breadth early on · Speed matters, but learning matters more · Find pain so sharp that users will climb walls to solve
Airbyte isn’t just a startup. It’s the culmination of a decade-long apprenticeship in data, ambition, and human-first leadership. As Michel’s vision plays out, the next era of data won't be moved by scripts, but by autonomous intelligence unlocking organizational gold.
Key Takeaways
Michel’s decade-long experience across multiple startups, culminating in $415M worth of exits, prepared him to build Airbyte with deep operational and technical insight. · He learned that founders should explore markets they truly understand. His success with Airbyte came from staying rooted in his expertise: large-scale data systems. · At LiveRamp, rideOS, and Airbyte, Michel proved that small groups of motivated, mission-aligned people can outperform larger organizations by focusing on clarity and ownership. · Michel distinguishes between community traction and monetizable demand, understanding that open-source success (project-market fit) must evolve into business value (product-market fit). · Airbyte’s growth accelerated when it offered enterprises full control over their data, solving one of the most pressing privacy and compliance concerns in the AI era. · Raising $185M didn’t mean scaling recklessly. Michel emphasizes experimentation hygiene, investor alignment, and measured growth before expanding aggressively. · From hacking as a teen to building data platforms, Michel’s story shows that curiosity, humility, and relentless learning are the real superpowers behind sustainable entrepreneurship.
Bio
Michel Tricot is the co-founder and CEO @ Airbyte. He has been working in data engineering for the past 15 years. As head of integrations and engineering director at Liveramp (NYSE: RAMP), he grew the team responsible for building and scaling the data ingestion and data distribution connectors, syncing 100s TB every day. In 2020, he co-founded Airbyte, the new open-source data integration platform, with the vision to commoditize data integration pipelines across all industries and organizations. After just 1 year, Airbyte grew a community with more than 6k members, got deployed over 16k times and raised over 180M from Accel, Altimeter, Benchmark, Coatue and YC.
Original Version
Alejandro Cremades: All righty, hello everyone and welcome to the DealMaker Show. Well, today we have an amazing guest and I hope that you're all ready for the battle of accents. and So it's gonna be quite fun, you know, it's gonna be quite an inspiring conversation. We're gonna be talking about the building, the scaling, the financing, the exiting.
Alejandro Cremades: ah He's also been part of two acquisitions as well you know in companies that he was at, one for $300 million that was acquired, another one for $115 million, and now he's actually raised for his company $185 million and doing something really interesting, especially you know on that transition of project market fit to product market fit. I think that you guys are all going to be really enjoying you know what our guest has to say. So without further ado, let's welcome our guest today, Michel Tricot. Welcome to the show.
Michel Tricot: Hi everyone. Thank you, Alejandro, for having me.
Alejandro Cremades: So born in Switzerland. and So give us a walk through memory lane. How was life growing up in Switzerland and all the above?
Michel Tricot: Yeah. Switzerland. I mean, obviously very biased by my childhood memory. It's an amazing country, beautiful, uh, and very close to the mountain. So I was put on skis very early on in my life.
Alejandro Cremades: and you and you And you moved quite a bit too.
Alejandro Cremades: I mean, I'm wondering, you know, going to Strasbourg from Switzerland and then Paris. I wonder, like, moving like that, what kind of perspective opened up early on for you?
Michel Tricot: um I think you get less attached to locations and more to the to the people around you. And also, you know, as you're moving, it also makes you have to list up leave some friends in your original country.
Michel Tricot: And i think it reinforces also your ah relationship with your family. So Strasbourg was a great time. It's a beautiful city. And Paris, I mean, amazing as well.
Alejandro Cremades: Amazing, for sure. For sure. Now, computer science. How do you get into the whole computer thing?
Michel Tricot: Yeah, that's a very good question. When I was in Switzerland, actually, very good friends of my parents had this big um room full of computers. So I would spend like all my weekend with them. I did not have a computer at the time.
Michel Tricot: And yeah, I was just playing Prince of Persia, Tetris, and just hacking around a few a few things. And as I was in Strasbourg later on, I got my first computer from like someone was getting rid of something that was a 386 or something like that. And yeah, that's when I started to really dive a little bit deeper.
Michel Tricot: And when I was end of middle school in France, you can work in farms. And so I went to work in a farm, harvesting tobacco. And that's how I bought my first computer and at the beginning, a little bit in programming, a little bit in hacking, et cetera, et cetera. So that was my my initial journey into it. And yeah, end of high school had to decide between, do I want to go for like the human machinery? So on the medical field, or do I want to go on the Silicium
Michel Tricot: ah ah in ah machinery? And that was CS and I went for CS.
Alejandro Cremades: And you you eventually came here to the U.S. too at Princeton, you know, working there with a understanding the brain, understanding the brain out of all things and et cetera.
Alejandro Cremades: So how was that, the you know, coming to the U.S., the American dream, you know, all of that good stuff?
Michel Tricot: Yeah. Now the, the, the end of your master in most, uh, French engineering school, you have to go. work for like a, a company or like to do an internship for like about six months.
Michel Tricot: And i was very fortunate that, uh, Siemens had a ah program where they would bring in like international interns and have them work with a researcher from, uh, from Princeton.
Michel Tricot: And she had worked on, uh, computer vision algorithm for segmenting the brain. And all of that was a product that we were selling to hospital and, and all the, um, like brain surgeon, etc. And it was really the ability to detect what part of the brain is where, what does it look like, what is the shape.
Michel Tricot: And also with like some specific modality, you could see disease appearing on the brain. So that was a very, very ah fun moment. ah American dream. I still remember the first time i landed in New York.
Michel Tricot: ah Big buildings, very wide roads, a lot of lights.
Alejandro Cremades: I hear you. Man, that's shocking. I mean, I still even remember, you know, they they I had that same feeling. i mean, it's it's quite shocking. Now, for you, quite heartbreaking, you know, the whole visa nonsense that you had to to deal with.
Michel Tricot: Yeah. I don't know if I would call it nonsense. For me, it's more, you it's like it's like a filter looking for for motivated people.
Michel Tricot: But yes, indeed, I had to go back to Paris mid-28, 2008. But actually, that was ah bad that became a very good because that was very much my first ah experience in the manufacturing of data.
Michel Tricot: I was at a company called FactSet, so also US company. And so I was doing some back and forth between ah New York and and Paris at the time. And yes, that's really when I learned like the fundamentals of what does it mean to collect data at scale, prepare it, and then ah making it actually actionable for um for like the end user. So here it was like traders and and quantitative analysis. So very, but that was a very, very good experience.
Alejandro Cremades: So how do you go from that to landing back in San Francisco and and joining as one of the early employees at LifeRamp?
Alejandro Cremades: Because say it sounds quite the ah transition there.
Michel Tricot: Yeah. I mean, I always wanted to go back to the US. Um, and i also wanted to be, ah in San Francisco in the Bay area because this is really where a lot of the tech is happening and where all the talents are going.
Michel Tricot: And yeah in 2000, I remember, ah December 31st. ah two thousand 2010, was with my now wife and we said, okay, we're going to change something in our life.
Michel Tricot: We're going to get married, e etc. And cherry on the cake. We're also going to be moving. Let's try to move into into the US. s ah in San Francisco. So I called a few friends that I went to college with. We had a very, very strong group over there where we did all our school project together.
Michel Tricot: And one of them had just joined LiveRump. At the time it was called Rap Leaf. And he said, yeah, ah let's try to see if that works. And at the time, visas were a little bit easier to get and I got it. And October 2011,
Michel Tricot: eleven landed in San Francisco with three suitcase. And that was the beginning of the journey.
Alejandro Cremades: How many employees were at LifeRamp when you joined?
Michel Tricot: Yeah. So it was between 25 and 30 people, uh, and they had an initial product, the reactive product, but also internally, they have started to pivot more into the, the ad tech, uh, well, so how do you.
Michel Tricot: move data between different like advertising platform to better target ah users online. So we are not doing anything that is advertising related, but we are moving all these pieces of information so that the the advertising or like the all the different things that you see online is very well suited to the to the audience.
Michel Tricot: And here working at internet scale, as you can imagine, when you're in ad tech, you basically are on so many websites, so many calls, so many, uh, like we're processing like petabytes of data.
Michel Tricot: And to me, that was, I went from like the manufacturing of data to how do you manage very, very large scale, um, uh, that assistance, uh, and yeah
Alejandro Cremades: I mean, 20 or so employees, you know, it it' say definitely gives you a glimpse of what are what are some of the ingredients that they ended up making the company becoming a success because it ended up being acquired for over $300 million.
Alejandro Cremades: I guess if you had to, like, look back, you know, and and reflect, what would you say were the top three three things that actually made that company the success that it became?
Michel Tricot: so the first thing would definitely be right place, right time. That was really the explosion of mobile and i know internet had started earlier, but that really became like completely widespread.
Michel Tricot: You’d have an automated way of mining the data gold in your organization. Accessing data should be a no-brainer. Today, it requires large teams to manage and integrate it.
Michel Tricot: I just want an agent to move through an organization, discovering, “Oh, you’re using this tool,” “You’re using that database,” and be able to autonomously decide what data to pick, move, and integrate into its processing.
Michel Tricot: Basically, scaling how you make data actionable — without humans constantly applying judgment — through automated intelligence that knows how to operate across massive volumes of data.
Alejandro Cremades: That’s amazing. So obviously we’re talking about the future here. I want to talk about the past, but through the lens of reflection.
Let’s say I bring you back to 2019 — when you gave your notice after the RideOS acquisition and were about to figure things out. If you had the chance to go back to that moment and give your younger self one piece of advice before launching a business, what would that be and why, given what you know now?
Michel Tricot: I think as part of our exploration of what company or market we wanted to address, we spent time on areas where neither I nor my co-founder had a lot of expertise.
Michel Tricot: It’s easy to say in hindsight that maybe we shouldn’t have wasted time on those. If I were to go back and talk to my younger self, I’d say: “Man, you know what it means. You know the complexity of data. Just focus your exploration on any kind of data product. Don’t waste time on things you don’t know.”
Michel Tricot: But it’s easy to say in hindsight. We also learned a lot talking to people — self-driving car companies, banking and fintech companies. We may have wasted a bit of time, but we also gained valuable insights and learning from it.
Alejandro Cremades: That’s amazing. So Michel, for people listening who’d love to reach out and say hi, what’s the best way to do so?
Michel Tricot: First, we have a community Slack. On our website, you can join it — I’m available there. Otherwise, I’m also on LinkedIn. I try to give a window into the life of the company to the outside world.
Michel Tricot: As an open-source company, it’s very important that people are part of the story. We’re not the only ones creating it. So I’d say those are the two main channels.
Alejandro Cremades: That’s amazing. Well, Michel, thank you so much for being on The DealMaker Show today. It has been an absolute honor to have you with us.
