VeryAI raised $10M led by Polychain to build palm‑print biometrics and cryptographic ID infra that helps exchanges, airdrops, and DAOs filter bots, deepfakes, and Sybil attacks at scale.
Summary
- Polychain led the 10M dollar round, joined by the Berggruen Institute, Anagram, and Solana co-founder Anatoly Yakovenko, signaling strong crypto‑native and policy backing.
- VeryAI positions itself as “identity verification infrastructure,” using palm‑print biometrics plus cryptographic ID so apps can gate real users without storing raw biometric data.
- The stack targets exchanges, airdrops, social apps, and on‑chain governance, aiming to power Sybil‑resistant voting, fair token drops, and anti‑fraud controls in DeFi and NFT markets.
Identity verification startup VeryAI has raised 10 million dollars in fresh funding to build palm-print biometrics and cryptographic ID tools aimed at filtering bots, deepfakes, and synthetic identities at internet scale, according to an official announcement.
Polychain leads $10M round into biometric, crypto-ID stack
VeryAI said the 10 million dollar financing round was led by Polychain Capital, with participation from the Berggruen Institute, Anagram, and Solana co-founder Anatoly Yakovenko among other angel backers. The cap table signals clear alignment with both top-tier crypto VCs and ecosystem builders who are already wrestling with spam, Sybil attacks, and AI-generated identity fraud across Web3 and social platforms.
The company describes itself as “identity verification infrastructure,” positioning its stack as a base layer that apps, protocols, and platforms can plug into rather than a consumer-facing KYC widget. That framing puts VeryAI directly into the emerging “proof-of-humanity” arms race, where on-chain identity, real-user gating, and compliance increasingly collide with privacy and decentralization ideals.
Palm biometrics plus privacy-first verification
VeryAI is developing a privacy-first verification system built around palm-print biometrics combined with cryptographic identity technology, rather than traditional document uploads or face scans. The goal is to let services distinguish real humans from bots, deepfakes, and synthetic identities without exposing raw biometric data, hinting at the use of techniques like zero-knowledge proofs or secure enclaves to keep underlying signals private.
The project explicitly targets internet-scale deployment: think exchanges, airdrops, social platforms, and on-chain governance all needing a reliable “one-person-one-account” primitive in a world flooded by AI agents. For crypto, this kind of infrastructure is directly relevant to Sybil-resistant voting, fair token distributions, and anti-fraud controls in DeFi and NFT markets, while giving regulators and institutions a story that isn’t just surveillance-heavy KYC.
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