Most on-chain AI projects ask you to trust their off-chain black box. @OpenGradient refuses to.
Their HACA architecture combines zkML proofs and Trusted Execution Environments (TEEs) to solve the "AI trust problem" at its core. Here is why that matters: zkML mathematically proves a specific model ran on specific inputs, while TEEs keep the inference process secure and isolated. You don't have to trust the node operator—you verify the computation.
With 500K+ zkML proofs already generated and 2M+ verifiable inferences, this isn't just theory. It's live infrastructure on Base, backed by a16z and Coinbase Ventures. Volume is currently $1M with a +3.4% 24h move as the market slowly wakes up to verifiable AI.
We post every algo signal's real result openly, and the full live track record + a free preview channel are in our bio/profile.
If AI execution can't be cryptographically verified on-chain, does it even belong in Web3? $OPG #OPG
Their HACA architecture combines zkML proofs and Trusted Execution Environments (TEEs) to solve the "AI trust problem" at its core. Here is why that matters: zkML mathematically proves a specific model ran on specific inputs, while TEEs keep the inference process secure and isolated. You don't have to trust the node operator—you verify the computation.
With 500K+ zkML proofs already generated and 2M+ verifiable inferences, this isn't just theory. It's live infrastructure on Base, backed by a16z and Coinbase Ventures. Volume is currently $1M with a +3.4% 24h move as the market slowly wakes up to verifiable AI.
We post every algo signal's real result openly, and the full live track record + a free preview channel are in our bio/profile.
If AI execution can't be cryptographically verified on-chain, does it even belong in Web3? $OPG #OPG