Hey PH! 👋 I'm Ahmed, founder of AI Governor. The problem that led me here: our team was running AI agents in production — sales agents, support bots, data pipelines — and every time something went wrong, the question was the same: "What did the agent actually do, and can we prove it?" We had logs. But logs can be altered. We had observability tools. But they watch, they don't govern. None of the existing tools could: - **Block** an agent from executing when its budget ran out - **Hold** a high-risk action until a human approved it - **Prove** — not just claim — that the audit record was never altered So we built AI Governor. Under the hood it's a SHA-256 hash-chained WORM audit log, an OpenAI-compatible proxy, and a governance pipeline that runs before every LLM call. The audit chain is verifiable by anyone — no account needed — because enterprise customers need to hand a URL to their auditor, not a PDF that we generated. What surprised us most: **the adoption pattern**. Teams don't use it because compliance told them to. They use it because once you've had an agent go off-script and cost $4,000 in 6 minutes, spend caps become a reflex. Free tier is 500k tokens/month, no credit card. Happy to answer questions about the architecture — especially the PostgreSQL hash-chaining if anyone's curious.

AIGovernor

The control plane for AI agents — govern, audit, prove.

The control plane for AI agents — govern, audit, prove.