AI vendor risk assessment tools use AI to automate traditional vendor reviews. Enzai's third-party AI risk management does the opposite: it governs the AI risk that vendors introduce into your stack, with the same rigour you apply to AI you built yourself.

Enzai runs five discovery methods in parallel: procurement records, SaaS telemetry, browser signals, network traffic, and direct vendor disclosure through a shared portal. Together they surface the third-party AI estate, sanctioned and Shadow, into one catalogue.

Enzai's continuous monitoring detects the change through drift indicators, model-version metadata, or vendor disclosure, and triggers re-assessment automatically. The platform alerts the system owner and re-scores the system against your AI risk framework.

Enzai structures vendor catalogue, dependency mapping, and AI-specific risk assessment to evidence both EU AI Act vendor-risk obligations and ISO 42001 supplier controls. Your auditor sees per-vendor framework alignment with the supporting evidence in one place.

Enzai sits as the AI-specific layer alongside your existing TPRM stack. Workflow handoffs push into Jira, ServiceNow, and Slack natively, so vendor reviews surface where your team already works rather than requiring them to learn a new tool.

Most teams have an initial third-party AI inventory inside 30 days through Enzai's discovery methods. Vendor cataloguing, dependency mapping, and continuous monitoring reach steady-state within 60-90 days, depending on the breadth of the vendor portfolio.