Zero-Knowledge Machine Learning (ZKML) Inference Verifier

[CORE IDENTITY] A zero-knowledge ML inference verification module that generates cryptographic proofs of model output correctness — enabling trustless AI inference verification without exposing model weights, training data, or proprietary architecture.

[TECHNICAL SPECIFICATIONS]

• Framework / Stack: ZKML proof generation layer, inference correctness verifier, ZK circuit compiler, on-chain/off-chain verification bridge
• Input Parameters: ML model specification, inference inputs, ZK circuit configuration, verification target environment
• Output / Execution: Cryptographic proof of correct inference, trustless verification certificate, on-chain/off-chain verifiable proof package

[DEPLOYMENT CONTEXT]

• Primary Environment: Trustless AI inference environments — blockchain, regulated AI deployments
• Target Persona: AI Engineers building verifiable ML systems, Compliance Teams requiring auditable AI inference

[SOVEREIGN COMPLIANCE] Instant digital fulfillment via automated webhooks.