The result loses scope, thresholds, artifacts, limitations, and review history.
Why FairMind exists
AI assurance has a continuity problem.
Tests happen in one tool, system identity in another, framework mappings in spreadsheets, remediation in tickets, and final review in a document assembled under deadline. FairMind exists to preserve that chain as evidence moves.
A vendor-neutral layer between evaluators and accountable governance.
Metadata stays metadata. Missing evidence stays missing. Review stays human.
The novelty is not another score.
FairMind’s product thesis is that trustworthy governance depends on durable relationships between evidence objects, decisions, and change over time.
Evidence Passport
A target exchange contract that binds the tested subject, evaluator, threshold, artifact, limitation, review, remediation, and superseding rerun.
Capability truth
Every evaluator declares validated, metadata-only, external-provider, unavailable, or insufficient-data state.
Reviewed mapping
Technical evidence can suggest a framework relationship. An accountable person decides whether that relationship is accepted.
Failure-preserving retest
A clean rerun supersedes the failed evidence without deleting what failed, who acted, or why the new result was accepted.
Framework-pinned manifest
The same accepted evidence can support several versioned frameworks while keeping the underlying technical claim bounded.
Built for skeptical reviewers.
FairMind should make it easier to reject an overstated claim, inspect its source, find the unresolved blocker, and reproduce the package—not merely make a dashboard look complete.
01Evidence before readiness
02Limitations beside results
03Human decisions with rationale
04Research claims bounded by measurement status
05Open interfaces before another closed evaluator
Bring your tests