Smart Model Router

Smart Model Router: practical plan

Routing policy

Task classes

• Summarization: choose a model meeting factual coverage and latency targets.
• Code assistance: select based on tested correctness, tool support and secure handling.
• Sensitive support: restrict to approved providers and data regions; minimize or redact input.

Decision inputs

Use task type, data sensitivity, context length, required capability, budget ceiling, provider health and quality scores. Avoid routing solely by cheapest token price.

Evaluation

Maintain a representative benchmark set per task. Track quality, hallucination/error rate, refusal correctness, p95 latency, cost per successful task and user correction rate.

Fallback

Define approved alternatives, timeout, retry budget and circuit-breaker behavior. Do not silently send sensitive data to an unapproved provider. Keep deterministic fallback where possible.

Governance

Version routing rules, log model ID and evaluation version without storing sensitive prompts unnecessarily, and obtain human review for material decisions.

Rollout

Run shadow traffic, compare quality and cost, then ramp gradually with rollback thresholds.

Measurement and review

Record the baseline, source, date range, denominator and owner. Use one primary measure plus quality guardrails; compare like-for-like cohorts and disclose missing data. Treat estimates as scenarios, not observed outcomes.

Risks and controls

Check relevance, consent, disclosure, workload and downside before scaling. Keep an evidence trail, obtain human review for material commitments, and pause if trust, quality or compliance signals deteriorate.

Next steps

1. Confirm the goal, audience and available capacity.
2. Gather the minimum evidence for a first test.
3. Assign an owner, budget and review date.
4. Run a small pilot, record outcomes and decide whether to iterate, expand or stop.