enterprise_baseline_v1
v1.0.3- E-1PII never leaves data class A.allow
- E-2Public claims require evidence.human
- E-3No model fine-tuning on customer data.deny
- E-4All material actions sealed in a receipt.allow
Enterprise AI governance needs more than policy documents. It needs operational controls inside the workflow: identity, data boundaries, model routing, policy gates, human approval, outcome grading, revocation, and receipts that show whether the workflow respected enterprise rules.
enterprise_baseline_v1
v1.0.3Useful for committees. Invisible to agents and workflows.
Once the tool is bought, the workflow is unmonitored.
Without grades and receipts, the only signal is escaped error.
If the agent has to be stopped today, no one knows how.
Versioned, signed, deployable. Reviewable by humans, readable by the runtime.
What can leave which boundary — at runtime, not in a wiki.
Local, hybrid, or cloud — based on policy, not engineering convenience.
Approve only where the policy says — no theater.
Audit packet for every workflow. SIEM-ready.
Tested like backups, not assumed.
A controller they command: custom rails over the estate they already run, policy gates on every route, and Actuality Receipts™ that prove the work. Human-at-the-Control stays in the architecture, so engineering authority scales with the estate.
The Team Control Sprint binds your policy as packs, enforces them at runtime, and proves it with receipts.