Third-Party Risk
Assess AI vendors, contracts, data exposure, controls, and ongoing monitoring.
AI Risk Intelligence & Vendor Management
AI vendor inventory, due diligence, model risk intelligence, third-party AI risk monitoring, residual risk tracking, scoring, and continuous surveillance for enterprise AI supply chains.
Buyer alignment
Assess AI vendors, contracts, data exposure, controls, and ongoing monitoring.
Make vendor decisions with evidence, risk rating, renewal posture, and remediation facts.
Track inherent risk, residual risk, scoring, and model-related exposure.
Understand vendor accountability, usage justification, and approval status.
Use cases
Create a governed register of AI vendors, tools, models, contracts, and owners.
Collect evidence, approvals, risk responses, and remediation before onboarding.
Assess inherent, residual, operational, privacy, security, and compliance risk.
Track changes in vendor posture, usage, obligations, and exception status.
Connect utilization, risk, evidence readiness, and renewal decisions.
Manage third-party and fourth-party AI dependencies across enterprise sectors.
Architecture & integration
Supports on-premises, private cloud, public cloud, or hybrid patterns depending on customer control, residency, and assurance requirements.
Regulatory and audit alignment
Supports vendor accountability, evidence collection, and ongoing control review.
Supports model usage inventory, exposure classification, and risk scoring workflows.
Creates reviewable vendor decision records for procurement, risk, and audit.
Applicable across financial services, healthcare, telecom, energy, technology, manufacturing, and government supply chains.
Next step
We can walk through product fit, architecture, pilot scope, deployment model, evidence expectations, and procurement review material.