Question 1

How does this work in a FedRAMP or classified environment?

Accepted Answer

The governance layer — enforcement receipts, provenance tracking, budget caps, kill switches — operates identically regardless of which AI inference backend is in use. For FedRAMP-boundary environments, the AI facade routes to cloud provider adapters through the normal FedRAMP-compliant data flow. For classified and air-gapped environments, the facade routes to an on-premises vLLM inference server running approved models on the customer's own hardware. No data leaves the enclave. The governance artifacts (receipts, provenance records) are stored in the same database as all other compliance data, inside the boundary.

Question 2

What happens when an agent exceeds its budget cap?

Accepted Answer

The agent invocation fails before the inference call is made. The budget check is a hard gate in the execution path, not a soft warning. The failure is logged as a governance event with the same permanence and receipt as any other governed action — so the audit trail shows both that the budget was exhausted and that enforcement fired correctly. The agent cannot proceed without explicit budget extension by an authorized operator. There is no "best effort" execution that proceeds and generates a warning afterward.

Question 3

Can I bring my own AI model and still get governed AI?

Accepted Answer

Yes. The BYOAI architecture is specifically designed for this. The vendor-neutral facade exposes a consistent interface that all 12 provider adapters implement. Your preferred inference backend — cloud-hosted or on-premises vLLM — is an adapter choice, not an architectural commitment. Provenance tracking, enforcement receipts, kill switches, budget gates, and JIT credential vending apply uniformly to all adapters. The governance properties do not depend on which provider runs inference.

Question 4

How does this compare to what Vanta or other GRC vendors offer for AI governance?

Accepted Answer

Vanta's "Agentic Trust" and similar vendor programs describe governance-adjacent product features — approval workflows, usage visibility, policy management. These are operationally useful. What they do not publish is a verifiable receipt format, a cryptographic chain structure, or a verification procedure that works without trusting their platform. Advisedly's enforcement receipts are auditor-independent by design: the verification procedure uses public key cryptography over an open envelope format, and an assessor with no platform access can verify the full chain. Ask any vendor claiming AI governance to show you a signed receipt for a specific action. The presence or absence of a usable answer is the clearest signal available about whether they have governed AI or an AI governance marketing program.