Use Case Foundry before Azure AI Foundry

Azure AI Foundry helps build and operate AI systems. Use Case Foundry helps decide what deserves to be built first, then turns workshop evidence into a roadmap, evaluation plan, and handoff package your delivery team can use.

See the workshop flow Review deployment readiness

What this establishes

The decision in view.

Principle 1

Run the discovery and prioritization work before committing engineering capacity.

Principle 2

Export a build-ready handoff with the workflow, evidence, tests, and human approval rules.

Principle 3

Keep the deployment boundary explicit: Foundry does not create credentials or push to your systems.

These tools belong in sequence, not in conflict

Use Case Foundry is for the decision work before implementation: which workflow matters, what evidence supports it, what makes it worth funding, what approvals apply, and how the pilot should be limited and tested. Azure AI Foundry is for building and operating the system after that decision is made.

A practical sequence

Run a use-case workshop or assessment in Use Case Foundry.
Review the evidence-backed roadmap and reject generic ideas early.
Choose one idea and define the agent design, test plan, and pilot limits.
Hand the package to the Azure delivery team for architecture, model, and environment work.

What the handoff should already contain

The workflow and business objective.
The evidence behind the priority.
The data and system assumptions.
The evaluation cases and pass thresholds.
The human-approval boundary and unsafe-action rules.

What this page is not claiming

Use Case Foundry is not Azure AI Foundry, and it does not replace implementation tooling. It helps teams arrive at Azure with a better problem definition and a more credible handoff.

Side by side

Compare the decision process.

Criterion	Use Case Foundry	Azure AI Foundry
Primary job	Choose which AI use case deserves a build and what must be true first	Build, orchestrate, and evaluate the chosen AI system
Best starting point	Strategy workshop, diligence, transformation review, or advisor-led assessment	After a use case, architecture, and evaluation approach are chosen
Output	Pre-assessment, ranked roadmap, test plan, and build handoff	Implementation environment, model and service tooling, and deployment workflows
Human control	Approval, evidence review, and pilot readiness are clear from the start	Execution tooling assumes the team has already defined the use case and controls