Designing an AI Evidence Gateway: Durable WAL, Portable MMR Proofs, and Bounded Formal Checks
AI gateways are often discussed as routing layers: authenticate a caller, apply policy, forward a request, and record what happened. For higher-assurance deployments, the harder engineering question is what evidence remains after a request completes—and exactly what that evidence proves. Aegis Latent Core is an AI Governance and Evidence Gateway for governed LLM traffic. Its current source…
The article discusses Aegis Latent Core, an AI Governance and Evidence Gateway for governed LLM traffic. It outlines the mechanisms and boundaries of the gateway, including request controls, bounded streaming redaction, durable evidence records, portable Merkle Mountain Range (MMR) inclusion proofs, Python and TypeScript integrations, and narrowly scoped formal checks.
The gateway sits between an application and a configured model provider, controlling access, enforcing input bounds, applying security measures, and recording evidence in a durable JSONL WAL. The article also mentions the use of Rust in the repository, specifically an optional native RustWal for auxiliary storage of terminal streaming frames.
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