AI vendor discovery
Create an evidence-backed census of approved, embedded, and previously unknown AI services across the digital supply chain.
- Known AI and model-provider taxonomy
- AI-shaped endpoints and agents
- Vendor ownership and concentration
AI third-party risk management
Manage AI riskbeyond contracts.
AI TPRM connects vendor diligence to observed behavior, revealing which services appear, what data reaches them, where it goes, and whether use still matches approval.
Product evidence
1st → NthAI recipient visibility
Policy ↔ Wirecontrol validation
Continuousvendor monitoring
Data and purpose risk
Determine which sensitive or linkable values reach each AI recipient and compare the observed purpose with the approved use case.
- PII, PHI, credentials, and trade-secret indicators
- Inference, embedding, recommendation, and decisioning
- Training-rights and retention context
Third- and fourth-party exposure
Follow the AI service beyond the named vendor to infrastructure, sub-processors, model APIs, and cross-border recipients.
- Downstream recipient chain
- Processing geography and sovereignty
- Concentration and dependency evidence
Ongoing assurance
Monitor approved AI vendors for new endpoints, sensitive-data paths, recipients, and disclosure gaps, then verify remediation through recurring evidence refreshes.
- Material-change alerts
- Before-and-after evidence
- Renewal and audit history
Data Risk Review
Turn AI vendor review into continuous evidence.
Start with one AI provider, enterprise domain, or vendor portfolio.
Request an evidence briefing Review slots are scheduled in the order requests are received.