Verification

A checklist for validating an enterprise AI platform on Vercel.

Use this checklist before treating the platform as ready for enterprise AI workloads.

Platform

Check	Pass condition
Architecture	Experience, control, runtime, async, and governance planes are named
Gateway	Model routing, fallback, and cost attribution exist
Workflow	Long-running tasks and approvals are durable
Sandbox	Risky tool execution is isolated
Queues	Batch and fan-out work has retry and poison handling

Quality

Check	Pass condition
Prompt contracts	Role, task, constraints, tools, and output schema are explicit
RAG	Retrieval respects permissions and freshness
Evaluation	Quality metrics run before release
Observability	Traces connect model, tool, latency, cost, and errors

Operations

Check	Pass condition
Security	Identity, secrets, WAF, provider policy, and approval gates are governed
Cost	Budget alerts and workload classes exist
Deployment	Preview, canary, rollback, and kill switch are ready
Incident	Owners, runbooks, and escalation paths are documented

References

Source categories for adapting the Vercel enterprise AI platform handbook.

Updates

Change log for the Vercel Enterprise AI Platform handbook.

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Platform Quality Operations