Decentralised AI Startup Pond Secures $7.5M Seed Round Led by Archetype

The company plans to use the funds to advance its AI platform including adding DeFi risk management and insider trading detection features.
Image source: cryptopond.xyz

Quick take:

  • The fundraising also attracted participation from Cyber Fund, Delphi Ventures, Coinbase Ventures and Near Foundation.
  • The company is building a comprehensive AI model ecosystem encompassing data, model computation, training, and inference.
  • Pond’s Web3 AI models are designed to power crypto-specific use cases driven by on-chain data.

Pond, a decentralised AI startup building a comprehensive ecosystem for training Web3 AI models has raised $7.5 million in a seed round led by Archetype. 

The fundraising also attracted participation from Cyber Fund, Delphi Ventures, Coinbase Ventures and Near Foundation, with Plume Network’s Chris Yin, Matrixport’s Cynthia Wu and Tesa Ho, the head of market research at Flashbots joining as angel investors.

The fundraising was structured as a simple agreement for future equity (SAFE) with token warrants, Pond co-founder and CEO Dylan Zhang told The Block.

Pond was founded in 2023 and initially leveraged on-chain data to allow users to explore the profiles of different crypto users and their connections.

“We achieved this through a proprietary graph algorithm designed specifically for blockchain data, which calculates the strength of these connections,” Zhang said.

The company is now advancing its offerings by developing a platform for building crypto-native AI models for different applications including security, recommendations and DeFi. Its new “complete model ecosystem” not only builds its own models but also supports others in model creation and commercialization, CTO Bill Shi told The Block.

According to Shi, Pond’s Web3 AI models are designed to 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 explained.


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