Evidence with citations
Every finding is grounded in a source document and section. Reviewers and auditors can trace any claim back to where it came from - not to a model's recollection.
A governed vendor-risk run, replayed end to end: source-grounded evidence, deterministic checks, then a human approval gate that rejects the vendor and writes a tamper-evident proof packet.
Read-only replay of an illustrative run - no inputs, no production credentials.
A real governed run, replayed in full below - ending in a human rejection and an auditable proof packet.
Eight events, exactly as the platform recorded them - from intake to a human approval gate that stops the run. Nothing is simulated past what you see here.
A vendor onboarding packet was submitted for governed review. The run is registered against flow vendor-risk/v3 and begins under the workspace's controls - every step from here is recorded.
Three documents were parsed and source-grounded evidence was extracted - each finding carries a citation back to the document and section it came from.
Rule-based checks ran against the required-document set. Most passed - but one required document is missing, which the gate later depends on.
Workspace policies were evaluated against the extracted evidence. One policy trigger fired on data residency.
The findings were combined into a composite vendor risk score. The score is elevated, so the run is routed to a human reviewer rather than auto-cleared.
Above the 60 review threshold -> routed to a human approval gate. No clearance is issued automatically.
A reviewer examined the run and rejected it at the approval gate. The vendor cannot be cleared, and the run stops here - no clearance is issued and no downstream write is performed.
The run ended exactly where governance required: a person decided, the decision is logged, and there is a proof packet anyone can audit later. No AI output reached a live system without it.
The replay is not a chatbot demo. It is the control plane doing its job: grounding, gating, and proof - the parts a regulator asks about.
Every finding is grounded in a source document and section. Reviewers and auditors can trace any claim back to where it came from - not to a model's recollection.
Elevated risk routes to a person, not an auto-approve. Here the reviewer rejected - and rejection is final at the gate. The run stops before anything is cleared or written.
The decision, the reviewer, the reasons, and the cited evidence are written once to an append-only audit trail. Months later, you can prove exactly why this vendor was not cleared.
PrivateFlow is not certified under any compliance framework. Controls are designed to support compliance preparation. Where the EU AI Act applies, high-risk obligations carry penalties up to the EUR 15M / 3% of worldwide annual turnover tier; this run is an illustrative, synthetic example.
We'll stand up a governed pilot on your own data - sandbox first, no production credentials required. You decide what the gates do.