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 implements provider-aware request controls, bounded streaming redaction, durable evidence records, portable Merkle Mountain Range (MMR) inclusion proofs, Python and TypeScript integrations, and narrowly scoped formal checks.
This article walks through those mechanisms and, just as importantly, their boundaries.
Version note: GitHub currently exposes a Release labeled v4.0.1, while the source anchors, all ten named Release assets, and the published SDKs identify version 4.0.0. The v4.0.1 ref points directly to a commit, making it a lightweight tag. Treat v4.0.1 as the GitHub Release label—not as evidence that the artifacts were rebuilt as 4.0.1, that the tag is signed, or that the tag-triggered publication workflows produced the public objects.
The request and evidence path
