Trust and governance
Make AI output reviewable before it enters commerce systems.
The competitive research is clear: trust matters as much as generation. Product Factory should present provenance, quality, approval, and access control as core product surfaces.
Quality
Completeness checks before export
Review
Draft, review, approve, reject
Access
Organizations, permissions, API keys
Human approval gates
Keep generated records in draft until a reviewer accepts the product for downstream export.
Quality scoring
Assess missing core fields and category requirements before a record leaves the workflow.
Workspace controls
Use organizations, member roles, permissions, and API keys to separate teams and automation.
Source retention posture
The app keeps generated records and can purge original source files after processing for local data minimization.
Next trust moat
Auditable enrichment beats generic AI copy.
The roadmap opportunity is field-level evidence: source span, modality, confidence, extraction strategy, and approval status for every important value.
- Trace every field back to source evidence
- Measure provenance coverage across records
- Track edit rate and approval throughput
- Keep export success visible by destination
Treat trust as product functionality.
The strongest buyers want faster records, but they also need to know which records are safe to publish.