From theblock by Yogita Khatri

Pond, a crypto startup building a decentralized AI model layer, has raised $7.5 million in a seed funding round led by Archetype.

Other investors include Cyber Fund, Delphi Ventures, Coinbase Ventures, Near Foundation and several angel investors such as Illia Polosukhin, co-founder of Near Protocol; Chris Yin, CEO and co-founder of Plume Network; Cynthia Wu, founding partner and COO of Matrixport; and Tesa Ho, head of market research at Flashbots, Pond said Thursday.

Pond began raising money for this round in April and closed it by July, co-founder and CEO Dylan Zhang told The Block. The round was structured as a simple agreement for future equity (SAFE) with token warrants, Zhang said, declining to disclose the post-round valuation.

What is Pond?

Founded in 2023, Pond initially built a user search engine powered by on-chain data, enabling users to explore blockchain connections. For example, if someone wanted to connect with Ethereum co-founder Vitalik Buterin, they could enter his ENS (vitalik.eth) and view who is connected to him in their network. "We achieved this through a proprietary graph algorithm designed specifically for blockchain data, which calculates the strength of these connections," Zhang said.

Over time, Pond saw the potential of a unified graph network across all types of on-chain data — social, financial and more — and expanded its focus to build crypto-native AI models for broader applications. "In the entire industry of AI, models are the engine that generates productivity," Pond co-founder and CTO Bill Shi told The Block. "By learning from and understanding data, models extract value from data and make predictions. Consider the current AI wave: It was unlocked by models like GPT and Llama."

Pond is now creating a "complete model ecosystem," encompassing data, model computation, training and inference. Shi said that Pond not only builds its own models but also supports others in model creation and commercialization.

User perspective

While web2 AI models like ChatGPT assist with tasks from text generation to recommendations, Shi said Pond's web3 AI models will power crypto-specific use cases driven by on-chain data.

"On-chain data is extremely messy and vast in quantity, making it incomprehensible to the human mind. By leveraging AI capabilities, we transform what is beyond human understanding into comprehensible information, helping users make better use of on-chain data," he said.

Currently, Pond supports applications in security, recommendations and DeFi.

In security, Pond has developed a graph-based model for predicting malicious addresses, achieving an accuracy of 0.936 and a precision of 0.935. This model will be available on Pond's platform and will be used by "an industry-leading security company," according to Shi.

In recommendations, Pond offers models that suggest NFTs to users on Zora and DeFi protocols on Gearbox.

In DeFi, Pond has developed a dynamic fee model that addresses a key issue for liquidity providers: determining optimal transaction fees, Shi said. "When an intended trade is predicted to potentially lead to losses for liquidity providers, the model increases the transaction fee to compensate for the possible loss. Conversely, when a trade is predicted to be beneficial to liquidity providers, the model can lower the transaction fee to encourage more of these trades," he explained.

Pond plans to expand its crypto-AI use cases to include DeFi risk management, insider trading detection and personalized recommendations. Currently employing 11 people, Pond is actively hiring for roles including chief operating officer, product manager and ecosystem growth manager, Zhang said.

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