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Enterprise AI Patterns

Enterprise AI works best as a governed evidence flow, not as an unreviewed model answer.

The Pattern​

  1. Load approved sources through Data and preserve their identity.
  2. Assign bounded review areas to prepared Agents.
  3. Produce structured findings with evidence and open questions.
  4. Keep consequential decisions with qualified reviewers.
  5. Use Workflows only after the reviewed sequence is stable.
  6. Apply access, approval, and audit controls from Security and Governance.

Governed data and intelligence layers for enterprise use cases

Example​

A proposal review can extract requirements, map each response to source evidence, flag omissions, route questions to specialists, and prepare a readiness report. The accountable procurement, legal, security, and business owners still approve the decision.

Checklist​

  • Source owners and access boundaries are approved.
  • Every finding can point to evidence or an explicit unknown.
  • Specialist agents have narrow purposes and appropriate tools.
  • Workflow approvals and failure owners are defined.
  • Review quality, missed requirements, and incidents are measured.

Start with a read-only pilot and representative hard cases. For a failed user flow, continue with Troubleshoot Common Problems. Admins can use Data Governance for sensitive sources.

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