A deterministic coding-agent runtime for repeatable, auditable AI software engineering.
https://github.com/arman-jalili/rigorix-oss ↗// readme
Rigorix
The LLM generates code. Rigorix governs execution.
Coding agents can now write, edit, and ship software. The question organizations are starting to hit is not can they? — it’s what did the agent do, who approved it, and what was it allowed to touch?
Conversation history can’t answer that. An API gateway can’t either — that layer governs what flows into your AI, not what the agent does in your repository, your shell, your CI.
Rigorix is the enforcement layer for agent execution. Natural-language tasks are compiled into a reviewable plan, executed inside policy, permission, and budget boundaries, and every step is recorded in a signed, timestamped audit envelope. When an agent wants to do something risky, Rigorix doesn’t ask — it refuses, or gates the step for human approval.
Built for platform and security teams running agents at scale — not for developers who want a faster autocomplete.
Watch it stop
The fastest way to understand Rigorix is the two-minute demo: a coding agent fixes a real double-charge bug in a payments webhook — then its plan drifts toward a file it wasn’t cleared to touch…