Migration Guide
Move from prototype AI features to a governed Vercel enterprise AI platform.
Key takeaways
- Migrate from prototype AI features to a governed platform in stages, moving the most risky and valuable flows into platform primitives first rather than rebuilding everything at once.
- The stages run inventory, standardize, isolate, durable, async, and govern, each with a concrete output like a Gateway route, Sandbox boundary, or Workflow execution.
- Prioritize flows that are customer-facing, high-cost, high-volume, high-risk, or hard to debug.
- A flow is done migrating only when it has an owner, route policy, runtime boundary, logs, evaluation, fallback, and incident path.
Migration should reduce operational risk in stages. Do not rebuild every AI feature at once; move the most risky and valuable flows into platform primitives first.
Migration Stages
| Stage | Goal | Output |
|---|---|---|
| Inventory | Know what exists | AI system register |
| Standardize | Centralize model access | Gateway routes and owners |
| Isolate | Move risky tools | Sandbox boundaries |
| Durable | Move long tasks | Workflow-based execution |
| Async | Control volume | Queues and retry policy |
| Govern | Measure and audit | Dashboards, evals, evidence |
Prioritization
Start with flows that are customer-facing, high-cost, high-volume, high-risk, or hard to debug.
Exit Criteria
Each migrated flow has owner, route policy, runtime boundary, logs, evaluation, fallback, and incident path.