How Kite AI is Building the Foundation Layer for Global AI Development

In an era where artificial intelligence is reshaping industries at breakneck speed, few companies are tackling the fundamental infrastructure challenges that could either accelerate or bottleneck AI's global adoption. Kite AI, led by former professional speed skater turned tech innovator Chi Zhang, which is building what they call the "coordination layer" for AI development. In this exclusive interview, Zhang shares how his unique journey from sports to tech influenced his vision for democratizing AI resources and ensuring fair attribution in the rapidly evolving AI landscape.

Ishan Pandey: Hi Chi Zhang, it's a pleasure to welcome you to our 'Behind the Startup' series. Please tell us about yourself and what inspired you to create ZettaBlock and Kite AI?

Chi Zhang: Thank you, Ishan, it's great to be here. My journey started at the intersection of big data and AI, working on scalable infrastructure at Databricks and advancing AI automation at dotData. These experiences gave me a front-row seat to both the immense possibilities and the bottlenecks in leveraging data and AI at scale.

ZettaBlock was born out of a need to bring transparency, reliability, and accessibility to blockchain data. We built ZettaBlock as a scalable, developer-first solution that addresses the complexity of working with blockchain and AI datasets, making them more usable and actionable. While ZettaBlock focused on empowering developers and businesses with tools for data infrastructure, we recognized an even broader challenge: the lack of fair and open access to essential AI resources like data, models, and agents.

This realization led to Kite AI. Kite AI takes ZettaBlock's expertise in infrastructure and expands it into the AI space by building the coordination layer for global AI development. Our goal is to democratize access to AI resources while ensuring contributors—whether data providers, model developers, or end users—are fairly attributed and rewarded. Kite AI isn't just a platform; it's a foundational layer that fosters collaboration and drives the next wave of AI innovation.

Ishan Pandey: Could you elaborate on what it means to build the "foundation layer" for AI and how this layer impacts the broader AI ecosystem?

Chi Zhang: Building the "foundation layer" for AI is about establishing the essential infrastructure that powers the global AI economy—just as the internet provided a foundational layer for the digital age. At Kite AI, this means creating a coordination layer that connects data, models, and agents in a decentralized and transparent way, ensuring all participants can share, contribute, and monetize AI resources fairly.

This coordination layer solves two major challenges: Fragmentation: The AI ecosystem today is siloed, with resources scattered across platforms, institutions, and private entities. Kite AI provides a unifying framework for collaboration. Fair Attribution: Contributors often lack mechanisms to receive credit or compensation for their work. By embedding transparent attribution and reward systems, Kite AI ensures fairness and incentivizes innovation.

In essence, this foundation layer creates a shared infrastructure that enables the broader AI ecosystem to thrive by lowering barriers and fostering collaboration.

Ishan Pandey: With your experience in big data at Databricks and AI automation at dotData, how do you see the intersection of these fields evolving in the next decade?

Chi Zhang: The intersection of big data and AI will move toward seamless, real-time systems powered by a decentralized infrastructure. In the past, the focus was on collecting and processing massive datasets; now, it's shifting to curating, sharing, and utilizing these datasets collaboratively. AI automation, including AutoML, will play a critical role in making these processes more accessible to a wider audience.

Kite AI is positioned at this intersection, building the coordination layer that enables these systems to operate transparently and collaboratively. In the next decade, we foresee an ecosystem where AI and big data are no longer confined to individual organizations but are part of a shared, decentralized infrastructure that drives innovation globally.

Ishan Pandey: How do you view the role of AutoML in democratizing AI and empowering non-technical users?

Chi Zhang: AutoML is a transformative technology that simplifies the complexities of AI development, enabling non-technical users to create and deploy models. However, its effectiveness depends on access to high-quality, diverse datasets—something that is often limited today.

This is where Kite AI comes in. By providing a decentralized coordination layer, we facilitate access to a broader pool of AI resources, including data and models. This not only empowers non-technical users but also enables AutoML tools to deliver more accurate and inclusive outcomes.

Ishan Pandey: How does Kite AI ensure fairness and inclusivity in access to AI assets, and what ethical considerations guide your work?

Chi Zhang: Fairness and inclusivity are at the core of Kite AI's mission. Our decentralized architecture ensures that everyone—whether a data provider, developer, or user—has access to AI resources and is fairly rewarded for their contributions. The coordination layer we've built ensures that attribution is transparent and automated, reducing the potential for exploitation or bias.

Ethically, we prioritize transparency, privacy, and accountability. For example, our systems allow contributors to define how their data or models are used, ensuring that they retain control over their intellectual property. By embedding these principles into our design, we aim to set a new standard for fairness and inclusivity in the AI ecosystem.

Ishan Pandey: How has mentoring early-stage founders at StartX influenced your leadership style and the way you approach building startups like Kite AI?

Chi Zhang: Mentoring founders at StartX taught me the importance of adaptability, empathy, and clarity of vision. Every founder brings unique challenges and perspectives, and understanding their needs helped me refine my approach to problem-solving and leadership.

At Kite AI, I apply these lessons by fostering a culture of ownership and collaboration. Our team operates with a shared vision, but everyone has the freedom to innovate within their domain. This balance of structure and creativity is something I've carried forward from my time at StartX.

Ishan Pandey: With increasing global focus on AI regulation, how is Kite AI preparing to navigate compliance while ensuring innovation, and what role do you think regulatory frameworks should play in shaping the future of AI?

Chi Zhang: AI regulation is both a challenge and an opportunity. While it's essential to protect users and ensure ethical practices, overly restrictive frameworks can stifle innovation. At Kite AI, our decentralized and transparent coordination layer is designed to align with global compliance standards while fostering open collaboration.

We believe regulatory frameworks should focus on promoting transparency, accountability, and inclusivity. By creating environments where innovation can flourish within ethical boundaries, we can unlock AI's full potential without compromising on safety or fairness.

Ishan Pandey: In your opinion, how will AI continue to reshape industries in the next five years, and what specific role do you envision Kite AI playing in this transformation?

Chi Zhang: AI will transform industries by automating processes, enabling smarter decision-making, and personalizing user experiences. In the next five years, we'll see more industries leveraging AI not just for efficiency but also for entirely new business models, from AI-driven marketplaces to autonomous systems.

Kite AI will play a pivotal role as the coordination layer that democratizes access to AI tools and resources, making this transformation accessible to a wider range of participants. By providing the foundation for fair and transparent collaboration, we aim to accelerate the adoption and impact of AI across industries.

Ishan Pandey: You have a unique background as a professional inline speed skater. How did this experience shape your leadership style or influence your approach to building a tech startup like Kite AI?

Chi Zhang: Speed skating taught me the value of discipline, precision, and resilience. In racing, success depends on preparation, strategy, and the ability to adapt to changing conditions—qualities that are equally important in building a startup.

At Kite AI, I've carried these lessons forward by fostering a team culture that emphasizes adaptability and long-term vision. Like in skating, building a successful company isn't just about speed—it's about endurance, focus, and the ability to navigate challenges with confidence.

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