Track third-party AI vendors and their compliance posture
Monitor your AI vendor ecosystem with structured risk assessments, review workflows, and compliance verification across multiple regulatory frameworks.
The challenge
Your AI supply chain is a compliance blind spot
Most AI systems rely on third-party vendors - but few organizations track vendor risk systematically. One vendor incident can impact dozens of AI applications.
You don't know what data your AI vendors access - PII, financial data, health records, or proprietary model weights could be at risk
Vendor incidents (breaches, outages, compliance failures) are discovered reactively, after they've already impacted your operations
No systematic way to assess vendor risk means some high-risk vendors operate with no oversight while low-risk vendors are over-audited
Regulatory requirements like GDPR, HIPAA, and EU AI Act extend to your vendors, but you can't demonstrate due diligence
When a vendor's status changes, you can't quickly identify which AI applications are affected for impact analysis
Contract terms, review dates, and compliance certifications are scattered across emails, documents, and memories
Benefits
Why use Vendor management?
Key advantages for your AI governance program
Assess vendor risk with 4-dimension scorecard (0-100 score)
Track review status through 4-stage workflow
Monitor regulatory exposure across 8 frameworks
Link vendors to multiple use cases with impact analysis
Capabilities
What you can do
Core functionality of Vendor management
Vendor registry
Maintain a centralized vendor directory with contact details, contract status, and compliance documentation.
4-dimension risk scorecard
Evaluate vendors across Data Sensitivity, Business Criticality, Past Issues, and Regulatory Exposure dimensions with weighted scoring.
Vendor review workflow
Route vendor assessments through Not Started, In Review, Reviewed stages with automated reminders for periodic reassessment.
Vendor risk register
Track vendor-specific risks with severity ratings, mitigation plans, and contractual safeguards.
Vendor trend analytics
Monitor risk score changes over time and track compliance posture across your vendor portfolio.
Insurance example
How an insurer managed AI vendor risk after a breach
See how organizations use this capability in practice
The challenge
An insurance company used 8 AI vendors across claims processing, fraud detection, and customer service. When one vendor experienced a data breach, they couldn't immediately identify which systems were affected, what data was exposed, or how to communicate the impact to regulators and customers.
The solution
After the incident, they implemented a structured vendor management system. Each vendor was assessed using a 4-dimension scorecard: the breached vendor scored 78/100 (high risk) due to PII access and high business criticality. All vendors were linked to their respective use cases, and review workflows were established with quarterly reassessment.
The outcome
When a different vendor later reported a minor security incident, the team immediately identified 3 affected use cases, assessed the data at risk (internal only, no PII), and completed their regulatory notification within 24 hours. The structured approach turned a potential crisis into a routine process.
Why VerifyWise
Structured vendor risk management for AI
What makes our approach different
Risk scorecard that makes sense
Four dimensions that matter: what data they access, how critical they are, their incident history, and regulatory exposure. Get a 0-100 risk score you can act on.
Impact analysis built in
Every vendor links to the use cases that depend on them. When a vendor has an issue, instantly see which AI applications are affected.
Review workflow that works
Move vendors through Not Started → In Review → Reviewed → Requires Follow-up. Track who reviewed what and when, with full audit trail.
Regulatory context
What regulations require
AI vendor management isn't just good practice - multiple regulations require it. Here's what you need to demonstrate.
Controllers must only use processors providing sufficient guarantees. You must have contracts covering data processing, security measures, and audit rights.
Importers and distributors of AI systems share compliance obligations. You must verify that providers have completed conformity assessments for high-risk systems.
Business Associate Agreements (BAAs) are required with any vendor accessing protected health information. You must assess their security practices and incident response capabilities.
The Vendor Management criterion requires organizations to assess, monitor, and manage risks from third-party service providers with access to systems and data.
Supplier relationships must include information security requirements, monitoring, and review. Changes to supplier services must be managed and risk-assessed.
Technical details
How it works
Implementation details and technical capabilities
4-dimension vendor scorecard: Data Sensitivity, Business Criticality, Past Issues, Regulatory Exposure
Risk score calculation (0-100) based on weighted scorecard values - higher scores indicate higher risk
7 data sensitivity types: None, Internal Only, PII, Financial data, Health data (HIPAA), Model weights/AI assets, Other
3 business criticality levels: Low (non-core), Medium (replaceable), High (critical)
3 past issues options: None, Minor incident, Major incident
8 regulatory exposure types: None, GDPR, HIPAA, SOC 2, ISO 27001, EU AI Act, CCPA, Other
Vendor risk assessment: 5 impact levels (Negligible→Critical), 5 likelihood levels (Rare→Almost Certain)
Review workflow: Not Started→In Review→Reviewed / Requires Follow-up with reviewer and date tracking
Many-to-many vendor-project linking with soft delete support for vendor risks
Field-level change history for vendors and vendor risks with user attribution
Supported frameworks
Integrations
FAQ
Common questions
Frequently asked questions about Vendor management
The scorecard evaluates vendors across 4 dimensions: Data Sensitivity (7 types from None to Health/HIPAA), Business Criticality (Low/Medium/High), Past Issues (None/Minor/Major incident), and Regulatory Exposure (8 frameworks). These combine into a risk score from 0-100, where higher scores indicate higher risk.
Vendors progress through 4 review statuses: Not Started (awaiting review), In Review (actively being assessed), Reviewed (assessment complete), and Requires Follow-up (issues identified needing action). Each status change is tracked with reviewer and date.
Each vendor can have multiple risks in a dedicated register. Risks are assessed on impact (Negligible, Minor, Moderate, Major, Critical) and likelihood (Rare, Unlikely, Possible, Likely, Almost Certain). Each risk has an action plan, action owner, and severity calculation.
Vendors link to use cases (projects) through a many-to-many relationship. One vendor can serve multiple use cases, and each use case can have multiple vendors. This enables impact analysis - when a vendor's status changes, you can see all affected AI applications.
More from Discover
Related capabilities
Other features in the Discover pillar
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