Pick work, not a model.
A model comparison is useful after the task is defined. Begin with a repeated job, the people doing it, the current time or error cost, and the decision the output supports. A workflow that saves ten minutes but creates twenty minutes of review is not an automation win.
Treat information handling as architecture.
Record every input, its purpose, where it is sent, who can access it, how long it remains and how a person corrects it. Your privacy or legal owner decides the required notices and lawful basis. A vendor setting is part of the control set, not proof of compliance by itself.
Evaluate with your real edge cases.
Create a compact set of normal, difficult and unacceptable examples. Score the output for the dimensions the business needs, such as factual accuracy, completeness, tone and correct escalation. Keep the set stable enough to compare model or prompt changes over time.
Design the human role.
Decide which outputs can proceed automatically, which need review and which must never be delegated. Give reviewers the source context and a clear correction path. If nobody owns exceptions, the workflow is a demo rather than an operating system.
Operate for model change.
Providers update models, prices and policies. Keep evaluation separate from the provider interface so alternatives can be tested. DLVX uses different models for different work and revisits the routing as the tools change. Client implementations follow the same principle: fit the workflow, constraints and existing systems.