Turn fairness review into a repeatable operating cycle.
Set the cadence for review, upload test results, document the scope of each audit, record exceptions, and route sign-off to the people who are actually accountable.
Bridgecairn Ledger
Three workflows that turn AI governance into daily operations.
Bridgecairn Ledger gives teams a practical way to review AI systems, keep a current inventory, and generate documentation from the same source of truth. The point is traceability and repeatability, not ceremony.
Core workflows
Purpose-built for the reviews and records teams already owe the business.
Each workflow is useful on its own, but Ledger is strongest when they stay connected. Reviews create evidence, inventories keep context current, and documentation pulls from the same underlying record.
Keep a living record of systems, dependencies, and ownership.
Track every AI system in use, who owns it, which vendor or model is involved, what documentation exists, and which reviews are slipping past their due dates.
Structured inputs become review-ready outputs.
Instead of rebuilding the same summaries by hand, teams can generate risk summaries, usage descriptions, governance records, review histories, and procurement responses from the data they already keep.
A shared operating record without the spreadsheet sprawl.
The system is designed to reduce coordination overhead while making ownership, review history, and supporting evidence easier to trust.
- A shared record across compliance, legal, security, and product
- Clear ownership with timestamped activity and approvals
- Fewer one-off requests for screenshots, exports, and status notes
Governance processes that decay the moment the quarter gets busy.
Bridgecairn Ledger is meant to remove the failure modes that make AI oversight feel performative instead of operational.
- Audit work scattered across inboxes, slide decks, and shared drives
- Inventories that go stale a week after someone exports them
- Documentation efforts that restart from a blank page every cycle