Review risky outcomes on a schedule that survives real life.
Define review cadence, upload test results, track exceptions, route approvals, and keep a clean record of what was tested across groups or use cases.
ASPM & AI Compliance
AI compliance work that looks like real operations.
Bridgecairn Ledger helps teams run bias audits, maintain a living inventory of AI systems, and generate usable compliance documentation without turning every review cycle into a custom consulting project.
What teams run in Bridgecairn Ledger
One operating layer for reviews, evidence, approvals, and audit trails.
Bias audits Schedules, evidence uploads, exceptions, approvals
AI inventory Owners, vendors, model changes, missing docs, reminders
Documentation Risk summaries, change logs, governance records, responses
Bridgecairn Ledger
Three practical workflows, connected inside Bridgecairn Ledger.
The goal is not theoretical governance. It is helping a company prove what it reviewed, what changed, who signed off, and what still needs attention without piecing the record together from five disconnected tools.
A living map of every AI system, not a dead spreadsheet.
Track systems in use, store owners and reviewers, record vendor or model changes, flag missing documentation, and remind teams when reviews are overdue.
Turn structured inputs into documents people can actually use.
Generate risk summaries, usage descriptions, change logs, governance records, review histories, and procurement responses from the same underlying system data.
What it replaces
Built for the practical compliance work most teams actually have.
Scheduled
reviews instead of ad hoc check-ins
Versioned
records of model, vendor, and policy changes
Assigned
approvals with named owners and reviewers
Usable
documents generated from structured evidence
“Most companies do not need a complex fairness lab. They need a workflow that keeps reviews, evidence, and approvals from falling apart.”
Compliance, security, legal, and product teams sharing one record.
Bridgecairn fits organizations that already have AI systems in use and need a reliable way to review them, track changes, and answer internal or external questions without rebuilding the same response every time.