Conversation Vana Founder - Anna Kazlauskas: From High School Dropout to Web3 Pioneer: How a Federal Reserve Intern is Reimagining Decentralized Data with Vana

TechFlow: Sunny

Vana: Anna Kazlauskas

Introduction

I first met Anna at an ETHcc side event organized by Flock.io. By then, I was exhausted from a full day of sessions, bombarded by discussions about the same trending projects and VC forums that were all starting to blend together. It had become somewhat monotonous. Then, Anna came on stage. Her style was refreshingly different from other Web3 founders—sharp, clear, and almost like a high school student passionately presenting her personal project. I stopped and stayed to listen to her talk.

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Interestingly, I had previously interviewed the founder of Flock, whose project also deals with decentralized data contribution, though Flock focuses on public data while Vana is centered around private data. A quick search on Twitter revealed that Anna was not some high schooler, but the founder of a decentralized AI project backed by top-tier investors like Paradigm and Polychain. This prompted me to set up a coffee interview with Anna’s co-founder, Art, to delve deeper into her journey.

Anna attended MIT, where she was classmates with the founders of Optimism, Blur, and Glow. In this interview, we explore how these brilliant minds navigate their lives and careers at the forefront of information, education, and capital.

About Vana

Vana is a decentralized platform aimed at revolutionizing data ownership and AI development in the Web3 space. Its core principles include:

• Data Ownership and Portability: Vana empowers users to control and manage their personal data, allowing it to flow freely across applications and be stored non-custodially, much like cryptocurrency in a wallet.

• Decentralized AI Development: Users can contribute data to train AI models and earn ownership stakes in the models they help create. Developers can access cross-platform data to build personalized applications and train advanced AI models.

• Data Liquidity and Monetization: Vana introduces Data Liquidity Pools (DLPs) to incentivize, aggregate, and verify valuable data. Users can monetize their data by contributing to these pools, treating data as a flexible, modular financial asset.

• Ecosystem and Applications: Vana is building a suite of decentralized applications and data collectives, including r/datadao for Reddit data, Volara for Twitter/X data, and Flirtual for managing dating app data.

• Technical Infrastructure: Vana has developed a Layer 1 blockchain designed for data transactions and privacy, supported by multi-layer architecture (including Data Portability and Data Liquidity layers) and the Universal Connectome, which maps data flows across the ecosystem.

Vana aims to empower users and foster innovation in AI by creating a new paradigm for data ownership, AI development, and value creation.

Interview Summary

1. From the Federal Reserve to Y Combinator: Anna shared her journey from interning at the Federal Reserve in high school to working at the World Bank, where she automated repetitive tasks, leading her to drop out and join Y Combinator to start her entrepreneurial path.

2. The Discovery of AI and Data Ownership: At MIT Bitcoin Club, Anna discovered the connection between AI and decentralized data, particularly the challenges of data quality and ownership. She and her co-founder launched Vana to help users benefit from the data they contribute.

3. Vana’s Mission and Technical Architecture: Vana is a decentralized platform focused on private data ownership, allowing users to monetize their data through liquidity pools and token mechanisms. Its Layer 1 blockchain ensures privacy and scalability for its users.

4. The Impact of Quantitative Thinking on Anna: Anna has always been attuned to numbers and probability modeling, a mindset that has shaped her unique perspective on AI and data systems. It drives her to explore how decentralized platforms and AI models can commercialize data.

5. Challenges and Opportunities in Decentralized Data: Anna explained the primary challenge in decentralized data ownership—helping users understand the value of their data—and how Vana’s unique token economic model addresses this while creating a self-sustaining data-driven ecosystem.

6. Vana’s Business Model: By leveraging a data transaction model and decentralized AI development, Vana treats data as a financial asset. Users can earn ownership of AI models through data contributions and profit from their value.

From the Federal Reserve Internship to Y Combinator—How Did Anna’s Entrepreneurial Journey Begin?

TechFlow: You interned at the Federal Reserve in high school and then worked at the World Bank the following year. How did these experiences shape your entrepreneurial journey?

Anna:

Yes, it all started at Central High School in Minnesota. I was really interested in economics, and getting an internship at the Federal Reserve at that age was quite rare, but I was very determined. I remember having a poster of Janet Yellen in my room! Later, when I got to the World Bank, I realized that many interns were doing repetitive tasks, and I wanted to simplify them through automation. I wrote machine learning software to help classify documents, and the results were more impactful than I expected. That’s when I realized how data and automation could transform large-scale organizational tasks. So, I dropped out of high school and joined Y Combinator—that’s how I got introduced to Silicon Valley.

TechFlow: What made you decide to drop out of high school and fully commit to entrepreneurship?

Anna:

It was a major decision at the time, but I realized that entrepreneurship was a huge commitment—almost a 5- to 10-year journey. I love the idea of solving problems, but not just automating documents forever. My real passion came from seeing how AI was evolving, and at the core of that is data quality and ownership. I began thinking about how decentralized systems like cryptocurrency could be applied to data ownership. That led to me and my co-founder, Art Abal, founding Vana. At the time, he was in grad school at Harvard.

The Intersection of AI and Blockchain—Anna’s Inspiration at MIT Bitcoin Club

TechFlow: Speaking of AI, when did you first realize the connection between AI, decentralized data, and crypto?

Anna:

My fascination with AI began when I was at MIT Bitcoin Club. I was really into econometrics and data modeling. In 2017, I came across the Attention is All You Need paper, which later became the foundation of ChatGPT. That’s when it hit me—everything in AI revolves around data, especially the quality and ownership of data. I wanted to find a way for people to truly own the data they contribute to AI systems. Since 2018, my co-founder and I have been exploring how users can benefit from the AI models built using their data.

Why Choose Layer 1?—Vana’s Focus on Private Data Ownership

TechFlow: I understand Vana is built on an EVM Layer 1 blockchain. Can you explain why you chose to build your own Layer 1?

Anna:

Vana is designed as a Layer 1 blockchain specifically for private data. This was a critical decision because it allows us to have tokens for specific datasets and models, which are fully programmable and EVM-compatible. This flexibility allows us to support any AI model or dataset while ensuring users can control their data. The Layer 1 architecture also helps address scalability and privacy concerns, which are essential for creating a sustainable ecosystem for decentralized data ownership. Since private data is incredibly valuable but hard to monetize in traditional systems, building Vana as a Layer 1 allows us to address data permission challenges while providing the infrastructure for large-scale AI applications.

The Role of Quantitative Thinking in Anna’s Vision for AI and Decentralized Data

In the interview, Anna also shared her personal background. Her father is a biochemistry professor, and her mother is a writer. Growing up, Anna was always drawn to numbers.

TechFlow: It sounds like you’ve viewed the world through a quantitative lens from a young age?

Anna:

Absolutely! I’ve always been fascinated by quantitative thinking. It’s not about creating a perfect model but making it useful—understanding how changing one element can lead to different outcomes. That’s why I have a unique perspective on AI and data systems today. For example, I love probability modeling, which is often used in baseball analytics. Rather than predicting a single outcome, you model various probabilities—like, what’s the chance of hitting a home run if the ball lands here? This mindset has helped shape my approach to AI and data systems.

TechFlow: In light of your quantitative thinking advantage, do you have any predictions for when Vana will break even?

Anna:

That’s a good question! Given our business model, breaking even depends on the scale of data contributions and the value of the AI models we build. Quantitatively speaking, we estimate that once we have around 100 million users contributing data and several high-value AI models generating revenue, we’ll be in a strong position to break even. The real challenge is ensuring a steady flow of data and developing commercially viable AI models. I think the exact timing will depend on user growth, AI model adoption, and overall demand for AI-driven solutions in the market.

TechFlow: What are the main challenges you’ve faced in building a company, especially in such a complex field like decentralized data ownership?

Anna:

One of the biggest challenges has been helping people understand the value of their private data. Early on, we tried compensating users with cash or stablecoins for their data, but they didn’t resonate with that. It almost devalued their contribution. Now, we’ve shifted to offering ownership of the AI models created with their data, which has struck a deeper chord. People want to feel like they’re part of something bigger, and the idea of owning a piece of an AI model is much more appealing. We saw this with Reddit Data DAO—nearly a million wallets registered, and about 140,000 passed proof of contribution, meaning they provided valuable Reddit data. That’s far more engaging than just offering cash.

TechFlow: Can you explain Vana’s business model and how it generates revenue?

Anna:

Vana operates on a data transaction model. Every time data moves through our network, a small fee—similar to Ethereum’s gas fees—is generated to cover the costs of running the network. As more users contribute their data and more AI models leverage that data, the system becomes self-sustaining. We’ve also patented our non-custodial data wallet and designed data liquidity pools and tokens for specific models. These tokens allow users to own both the datasets and the AI models derived from them, creating a system where users can profit from the value of their data. For example, through our Reddit dataset tokens, users can collectively own the dataset and any AI models built from it. As these models become more valuable, the users who contributed data will benefit from that value.

TechFlow: In such a complex system, how do you ensure people are motivated to contribute their data?

Anna:

We’ve had success through our data liquidity pools and model-specific token systems. For example, with our Reddit Data DAO, users can contribute their Reddit data and, in return, receive tokens representing ownership in both the dataset and any AI models generated from it. The key is making this tangible for people—they’re not just handing over data; they’re gaining ownership of a part of something bigger. We’ve moved away from cash rewards to something more meaningful: ownership in the AI models their data helps create. That has greatly increased user engagement.

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