Interactive product walkthrough
See the control tower around one AI decision.
Follow the path from a governed request to a named verdict, reviewer action, signed evidence and a change-impact decision. This is a read-only demonstration with illustrative data.
Demonstration environmentIllustrative records only · no customer data · no external calls · nothing is changed
Workspace / enterprise-ai
illustrative streamDecision stream
Systems12monitored
Control packs38active
Review queue2needs a person
Evidence100%chain complete
Recent governed decisions
What the tower is seeing
↳Select a decision to inspect its control result and evidence trail.
Named human action
SLA 4h · 2 openReview queue
Claims triage assistant
REVIEWHigh-impact recommendation · owner: Risk Operations
Clinical literature assistant
REVIEWIncomplete provenance · owner: Clinical Quality
Review records are ready for a named reviewer. In a customer deployment, the decision, reason, identity and resolution would be appended to the evidence chain.
Control lineage
3 requiring reviewChange impact centre
03
Enterprise AI Pack v3.2 → v3.3
REPLAY REQUIREDControl owner: Group Risk · effective 28 Aug 2026
Select a node to inspect its impact.The graph follows the evidence dependency, not just the software topology.
↳The tower tells the owner what changed, what is affected and which decisions need replay before release.
Independent verification
CHAIN HEALTHYEvidence register
✓
EK-04291 · signed decision record
REPLAYABLEInput digest · control pack v3.2 · verdict · reviewer state · timestamp
sha256: 4d7a…9c12✓
EvidencePack / 2026-08-27
COMPLETEPolicy, control, decision and change lineage records
offline verifier compatible↳Evidence is designed to remain checkable outside the application, including during procurement, audit and exit review.
From demo to pilot
Start with one consequential workflow.
Choose a bounded use case, run in shadow mode, agree the success criteria and produce a signed pilot report. The AWS environment is the next validation step—not a prerequisite for understanding the operating model.