Hi, I’m Carl. Here’s my bio in one sentence, one paragraph, and one thousand words.
I’m a founder and data scientist who helps organizations make smarter funding decisions for the public good.
I’m the cofounder of Kariba Labs, where we build technology to measure impact in the open. Our primary product, OSO, is an AI-native data platform that helps foundations, investors, and technology companies allocate capital and grow their ecosystems. I began my career in East Africa, first conducting soil science research, then launching a microfinance program, and eventually managing teams of business advisors for TechnoServe. I later moved to New York, where I helped multinational companies design economic development programs across their supply chains. In 2016, I cofounded Enveritas, which provides sustainability assurance for many of the world’s leading coffee and cocoa brands by combining more than 100,000 farm surveys each year with satellite imagery and machine learning. After a short stint at Protocol Labs, where I worked on funding models for open source networks, my cofounder and I left to start Kariba.
I’ve had an atypical path to where I am today, so this is my best attempt to retroactively connect the dots.
I started college on a computer science track but switched midway to environmental science, with a minor in Science in Society, a field that combined philosophy of science and economics. During a semester abroad, I lived in a village in northern Tanzania’s Rift Valley highlands. My senior thesis used satellite imagery and soil spectrometry to estimate erosion there.
I mailed the final report back to the village and … nothing happened. This was the first of many lessons in the difference between collecting data about a problem and doing something useful about it.
After graduation, I raised a few small grants and returned to Tanzania for what I fondly call my DIY Peace Corps experience. I learned Swahili and the basics of agroforestry, and eventually launched a microfinance program that grew to serve roughly 700 households. It was my first experience being responsible for a P&L and a team of people.
It also ended abruptly. At 24, I was fired, had my residence permit canceled, and had to leave the community where I had spent the last few years.
After a few months back home living with my parents, I found my way to East Africa again, this time for an international NGO called TechnoServe.
At the time, TechnoServe stood out among USAID-funded organizations for its belief that rural businesses, not aid alone, could create durable prosperity. In practice, that meant deploying business advisors to help enterprises like dairy plants and coffee mills secure financing, improve operations, and negotiate with buyers.
My first assignment was helping a network of coffee cooperatives improve their accounting, secure export financing, and sell to Starbucks. That work grew into a much larger effort across East Africa through the Gates Foundation-backed Coffee Initiative. I built out the initial monitoring and evaluation systems for the region and then launched the office in Ethiopia, where I was TechnoServe’s first employee on the ground. Over the next three years, we helped more than 160,000 farmers build new processing mills, access bank loans, and sell high-quality specialty coffee.
Many development programs struggle to produce durable results. The Coffee Initiative held up unusually well and later became a case study in how sustained execution, strong local teams, and market incentives can reinforce one another.
At the time, I attributed TechnoServe’s success mostly to its model and training methods. In retrospect, those mattered, but so did the unusually capable people willing to execute under difficult conditions. Some of my writing from the period captures the extraordinary adversity our business advisors overcame to help their clients succeed, as well as my own reflections from long drives down potholed roads.
While I loved the work, I did not love the expat culture among long-term international development professionals in cities like Addis Ababa and Nairobi. In 2013, I moved to New York to join TechnoServe’s newly formed Strategic Initiatives group, picking up an MBA at Columbia along the way. There, I worked with multinational companies and governments to design and implement economic development programs across global supply chains. The work required translating between very different worlds: farmers, banks, corporations, donors, field teams, and policymakers.
In 2016, I cofounded Enveritas, an idea hatched on a work trip to Cuba with a longtime colleague from TechnoServe.
We were trying to answer a difficult question: how can companies make credible “100% sustainable” claims given the challenges of working in supply chains with limited traceability and strong incentives for everyone to look the other way?
Our answer inverted the traditional auditing model. Instead of charging farmers for certification, we made verification free at the farm gate and sold the insights to the companies that needed them. We combined large-scale field surveys with satellite imagery and machine learning, and went through Y Combinator (S18) along the way. As COO, I was responsible for product, data, and engineering, as well as field operations in 30+ countries.
Today, Enveritas provides sustainability assurance for many of the world’s leading coffee and cocoa brands and conducts more than 100,000 farm surveys each year.
By 2022, I had spent more than a decade in coffee supply chains. Enveritas was on solid footing, with a staff of more than 80 and a global operating model, and I could feel myself searching for a new hill to climb. I was also spending the majority of my free time coding and doing data science on network graphs.
So I traded being the expert in the room for being a beginner again. I joined Protocol Labs, an R&D network and venture studio, with a broad mandate to explore funding models for open source projects. That work took me deep into public goods funding and experiments in rewarding open source contributions after the fact.
The deeper I went, the more I saw data problems that looked like coffee’s, only inverted. Coffee has mature markets for moving physical product and money through a supply chain. The hard part is tracing what happens between farms and end buyers. In software, dependency graphs make many of the relationships visible by default. The harder problem is determining which contributions matter, which teams need support, and whether funding them actually changes anything. There is no straightforward market for much of that work, and imposing one can distort the very thing you are trying to sustain.
After testing out several ideas at Protocol Labs, my cofounder and I left to start Kariba.
At Kariba, we work with foundations, investors, and technology companies to navigate complex ecosystems and make better decisions about growth and capital allocation. Our primary product, OSO, helps clients map the ecosystems they depend on, identify where value is being created, and decide where funding or attention can have the greatest effect. My current focus is building durable partnerships and growing a data science team that works closely with clients on difficult strategic questions.
Looking back, I’ve become less convinced that good ideas succeed on their merits alone. Outcomes are path-dependent. Ideas can remain latent for decades. My grandfather worked on game theory in the 1940s, but it took the better part of a century for many of those ideas to enter mainstream discourse. Progress depends on evidence, aligned incentives, capable people, and sustained execution. That may explain the pattern in my own career: I move on when the problems start to feel familiar, and I’m most invigorated when the right people and ideas have coalesced and the impossible starts to look merely difficult.
If you’re interested in connecting, reach out on LinkedIn or send me an email at carl dot cervone at gmail dot com.