Enterprises increasingly combine proprietary and open-weight models, hosted APIs, regional providers, and specialized smaller models. The right architecture may use several models behind one governed workflow layer.
Define the task and consequence of failure
Document input, expected output, languages, domain knowledge, latency, volume, autonomy, affected users, and downstream action. Quality requirements for drafting differ fundamentally from classification, extraction, coding, analysis, or operational decision support.
Translate governance into technical requirements
Assess data processing terms, location, retention, training use, identity, access, encryption, auditability, content controls, availability, change notification, and incident handling. Determine whether the use case requires hosted, dedicated, regional, or self-managed deployment.
Evaluate with representative work
- Build a versioned evaluation set from real task patterns.
- Measure accuracy, consistency, safety, latency, and cost.
- Review failure modes with domain specialists.
- Test prompts, retrieval, tools, and workflow—not the model alone.
- Repeat evaluation when models or system components change.
Design for a model portfolio
Separate business workflow, policy, knowledge retrieval, tools, evaluation, and logging from the model endpoint where practical. This makes switching and routing more realistic and reduces unnecessary dependency.
Maintain an approved model catalog with intended use, restrictions, owners, evaluation evidence, deployment pattern, and review date.
Select models with evidence.
Connect performance, governance, deployment, and lifecycle economics.