New York-based Pond, which uses AI and blockchain data for varied applications including security, has raised $7.5 million in a seed round led by Archetype. Other investors included Anagram, Coinbase Ventures, Inception Capital, Nonce Classic, Delphi Ventures and PAKA, and more than a dozen angel investors.
Co-founded by CEO Dylan Zhang, a former Huawei executive and alumnus of London’s UCL, and Chief Technology Officer Bill Shi, who earned a Ph. D. from the University of North Carolina at Chapel Hill, Pond’s says its team includes WeChat’s former machine learning architect, a former scientist at Amazon, and Yuga’s former principal data engineer.
New AI-Driven Use Cases
The funding is structured as a simple agreement for future equity (SAFE) with token warrants, Zhang told The Block.
Zhang in a LinkedIn post said his startup aimed “to build the AI model layer and fills the gap of crypto AI applications and infrastructure.” Over 30 project founders have joined the round as angels including Transformer co-author Illia Polosukhin, he added.
Besides using AI for crypto with graph foundation models, Pond says it is “pioneering” the applications of AI across crypto use cases, including trading, DeFi, security, maximal extractable value (MEV) recommendations.
Pond says a security model it co-developed with GoPlus has a 92% score “for both precision and recall in predicting malicious addresses.” Similarly, its Zora nonfungible token (NFT) recommendation model achieved a 52.8% score. Pond is also working on dynamic decentralized finance (DeFi) fees in collaboration with OpenGradient and on MEV solutions with projects like Mamori.
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Making Sense of On-Chain Data
“On-chain data is extremely messy and vast in quantity, making it incomprehensible to the human mind,” Shi told The Block. “By leveraging AI capabilities, we transform what is beyond human understanding into comprehensible information, helping users make better use of on-chain data.”
Whereas web2 AI models such as ChatGPT assist with text generation and recommendations, Shi said Pond’s web3 AI models would power crypto-specific use cases driven by on-chain data.
Initially, Pond built a search engine that allowed users to tap on-chain data to find people and create new connections by exploring their networks, similar to how people connect on LinkedIn. “We achieved this through a proprietary graph algorithm designed specifically for blockchain data, which calculates the strength of these connections,” Zhang said.
