Hao AI Lab launches cryptographic verification for LLM inference

Hao AI Lab launched a verifiable infrastructure framework for large language models on November 11, 2026. The system generates cryptographic proofs that inference computations followed the specified execution path, allowing external validators to check whether responses genuinely originated from the claimed model.

Agents generate proofs during inference, creating a mathematical audit trail for each token without exposing proprietary model weights. The framework prioritizes verifiability over speed, addressing limited visibility into models operating behind API endpoints or on third-party infrastructure. Enterprise customers can use these proofs to support compliance documentation and check delegated inference tasks.

Integration works through proof-generation hooks added to inference calls. An agent requesting a verifiable response receives both the output and a cryptographic proof object. Downstream agents or human operators can validate that proof using public verification keys before relying on the result, allowing evidence of authenticity to travel through multi-agent workflows.

Technical documentation describes the proof mechanisms and agent integration patterns, with implementation examples covering common enterprise deployment scenarios. The approach aims to provide inference accountability while protecting model providers’ intellectual property.