A developer arrives with a source API artifact — an Apigee XML policy bundle or a Tibco BusinessWorks project folder — and wants a working Mulesoft project. They hand the artifact to the migration workbench. The system parses the source, identifies every policy in play, retrieves the closest Mulesoft equivalents from its knowledge base, generates the target project, scores each policy mapping by confidence, and routes the result: high-confidence migrations go directly into a "completed" queue; low-confidence or structurally ambiguous migrations go into a "needs review" queue with annotations explaining what triggered the flag.
The developer reviews the flagged items. They see the source policy, the generated Mulesoft equivalent, the confidence score, and the reason for flagging. They approve, correct, or reject each item. Approved items are folded into the completed migration. Rejected or corrected items feed back into the system's policy mapping corpus — over time, human corrections become training signal that raises the confidence floor.
At scale, the workbench tracks migration state across all source APIs: how many are fully migrated, how many are in review, and how many are not yet started. This progress tracker is the operational interface for a migration program running across dozens or hundreds of APIs.
The system stops at generating the Mulesoft project. It does not deploy to a Mulesoft runtime, manage Anypoint Platform configuration, run integration tests against a live environment, or handle non-API Tibco artifacts (process orchestrations, adapters, message queues). Those are downstream responsibilities outside the workbench's scope.