GoKawiilConduct Runtime governance for AI agents — one policy enforces across every LLM call, every shell tool, every teammate's AI session.
Two product surfaces, one repo, one policy:
Conduct Guard — the policy engine. Decides block / warn / audit / inject for every AI action before it executes, backed by signed configuration and a hash-chained audit log.
— the policy engine. Decides for every AI action it executes, backed by signed configuration and a hash-chained audit log. Conduct Router — the LLM proxy. Point any provider SDK (Anthropic, OpenAI, Perplexity) at Router and every request runs through Guard on the way to the upstream provider.
Governance, not observability
Runtime firewalls like Straiker and Lakera tell you what an agent did. Guard controls what an agent can do — with cryptographic proof.
Runtime firewalls Conduct Guard Timing After the action Before the action Config integrity Trust the pack Workspace-signed Audit Log stream SHA-256 hash chain Coverage LLM calls only LLM and shell / MCP Failure mode Fail-open (soft) Fail-closed by default
The three-pillar moat:
Signed configuration — every workspace signs its active policy set. Every Guard check verifies the signature before enforcing. A tampered pack — pushed by anyone, at any layer — is rejected before it can decide anything. Hash-chained audit — every decision appends to a SHA-256 chain rooted at workspace genesis. Any missing or altered entry breaks the chain and is caught on one-click verification. Evidence you can hand to an auditor. Policy-first, not detection-first — rules decide before the action executes, with structured reasons. Not anomaly detection after the fact.
Discovery — the free wedge
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