Rigour Labs - Let AI agents move fast. Rigour keeps them under control.

I built Rigour because AI made me faster — but not necessarily more confident. As coding agents became capable of changing larger parts of a codebase, I kept running into the same problem: the smarter the agent became, the harder it was to understand everything it changed, verify every decision, and carry the lessons from one session into the next. I didn’t want another AI wrapper or another LLM judging an LLM. I wanted a deterministic layer around the agent — one that understands the codebase, limits blast radius, verifies observable work, produces evidence, and learns only from outcomes that were actually proven. That became Rigour. Today it connects context → agent actions → policy → verification → evidence → learning, and can govern high-impact MCP actions through a trusted gateway. The idea is simple: AI agents will keep getting more powerful. The engineering system around them needs to get stronger too. Rigour is my attempt to build that missing layer — open source and local-first.