Platform · AI Governance

Govern AI systems with evidence

CloudAnzen gives AI-native teams a system of record for models, vendors, use cases, risks, evidence, and customer-facing AI trust commitments.

AI governance module

Everything an enterprise buyer asks about AI, connected to proof

Replace scattered spreadsheets and ad hoc questionnaire answers with one governed workflow for AI system inventory, provider approval, model risk, evidence, and customer disclosure.

AI system inventory

Track AI features, use cases, owners, lifecycle stage, customer exposure, and the data classes each system touches.

Model and vendor register

Record model providers, versions, DPA status, retention terms, training posture, regions, subprocessors, and approval state.

Use-case approvals

Route proposed AI usage through security, privacy, and risk review before it becomes production behavior.

AI risk classification

Score risks such as data leakage, hallucination, prompt injection, missing human oversight, and unapproved model usage.

Evidence and model cards

Attach model cards, impact assessments, vendor reviews, policies, prompt logging records, and human oversight designs.

AI Trust Pack

Package your AI governance posture, approved models, data handling commitments, and Trust Center links for buyers.

Approval workflow

Make every AI use case reviewable before launch

CloudAnzen can turn AI intake into a repeatable workflow: classify the risk, request the right approvals, generate evidence tasks, and preserve the audit trail.

  1. 1Describe the AI use case and business purpose
  2. 2Declare customer data, PII, and sensitive data exposure
  3. 3Select the approved model or vendor
  4. 4Calculate risk tier and required reviews
  5. 5Attach evidence, model card, and vendor review
  6. 6Approve, approve with conditions, reject, or retire

Enterprise AI data control

Bring your approved AI provider and deployment model

BYOK, Dedicated Cloud, and BYOC options help enterprise teams keep AI workflows aligned to their procurement, retention, and data-governance requirements.

Bring-your-own-key for approved AI providers
Approved model/provider routing for sensitive workflows
Prompt and generation audit logs
Trust Center disclosures for data handling and AI governance