Feature · Vendor AI governance
Most enterprise AI risk is not in-house. It lives in the APIs you call, the vendors you contract, and the AI-embedded tools your teams use every day. SentinelAI gives compliance, risk, and governance teams a structured way to register, review, monitor, and evidence oversight of third-party AI — without relying on disconnected procurement spreadsheets and inboxes.
The third-party AI gap
Procurement teams sign contracts. Legal teams review terms. But the structured governance work — registering the vendor, mapping its AI systems to use cases, tracking due-diligence status, and evidencing ongoing review — rarely has a home. When auditors ask, teams reconstruct it from emails and slide decks.
SentinelAI treats vendor AI as a first-class governance domain. Vendor records link to the models they supply and the use cases those models support, so oversight can be tracked, evidenced, and reported from the same platform as internally built AI.
Governed vendor registry
SentinelAI's vendor registry brings together the context governance teams need to track — vendor identity, supplied AI systems, risk tier, review status, and linked business dependencies — in a searchable inventory instead of a shared sheet.
Core capabilities
These capabilities cover the recurring operational steps teams need when third-party AI is part of the governance scope.
Vendor record detail
Each vendor record keeps supplied AI systems, linked internal models, risk classification, contractual notes, review history, and assigned ownership together so due diligence starts from consistent context instead of ad hoc notes.
Due-diligence workflows
Run structured questionnaires, attach evidence, assign reviewers, and track unresolved gaps in one workflow so completion is comparable across vendors and evidence stays retrievable.
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Due-diligence workflow showing review steps, evidence attachments, and completion status
Risk tier and classification
Apply the same governance language used for internal models so vendor AI records can carry risk tiers, intended-use constraints, and policy-sensitive flags in a comparable operating model.
Ongoing review scheduling
Surface overdue assessments, expiring reviews, and stale vendor posture so governance teams can refresh oversight before changes become audit gaps or operational surprises.
Regulatory and framework alignment
The EU AI Act imposes requirements on deployers that use third-party AI. NIST AI RMF and ISO 42001 both address supply chain and third-party AI risk directly. SentinelAI maps vendor governance activity into the same evidence base used across the rest of the platform.
Framework mapping in SentinelAI is a governance support tool. It does not imply regulatory approval or third-party certification.
Vendor-to-model and vendor-to-use-case relationships
When vendor AI is linked to internal models and business use cases, governance teams can trace exposure, understand scope, and apply review decisions with confidence.
Vendor record → linked models and use cases
Who it's for
Vendor AI governance touches compliance, legal, procurement, risk, and governance — sometimes all at once. SentinelAI structures work for each stakeholder without requiring a separate tool.
Compliance officers and AI governance leads
Map third-party AI systems to framework obligations, collect structured evidence, and maintain a record of review decisions that survives personnel changes and audit cycles.
Risk managers
Maintain portfolio-level visibility of vendor AI exposure, review coverage, overdue assessments, and business dependency context without waiting for manual status rollups.
CISOs and security leads
Incorporate vendor AI supply-chain risk into the same governance operating model used for internal AI systems and model-level controls.
Legal and procurement
Access a structured record of which vendor AI systems are in use, under what terms, and with what due-diligence evidence before renewals or regulatory inquiries arrive.
How teams use it
Vendor governance is not a one-time procurement checklist. SentinelAI supports a repeating cycle of registration, review, linkage, and monitoring so oversight keeps pace with vendor AI change.
Step 1
Capture the vendor, supplied AI systems, ownership, risk tier, and initial governance context in one record.
Step 2
Collect evidence, assign reviewers, record decisions, and track unresolved gaps with a durable workflow.
Step 3
Connect vendor records to internal models and use cases, then refresh oversight as suppliers or dependencies change.
Continue exploring
Maintain a governed inventory for AI models and use-case context with lifecycle state, ownership, risk posture, and supporting evidence.
Operationalize evidence collection, control tracking, remediation, and framework mapping across AI systems.
Prepare executive reporting, audit-ready evidence views, and governance certificate workflows without overstating outcomes.
Start vendor AI governance
SentinelAI connects vendor registration, due-diligence review, model linkage, and framework mapping in one governed workflow. Evaluate it with a demo or explore independently.