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Intelligent Routing for Specialized AI Model Portfolios

Design governance, evaluation, and orchestration systems that route tasks across heterogeneous AI models while balancing cost, latency, and reliability.

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4. Designing Fallbacks and Escalations

No model is perfect. Build layered defenses to keep experiences resilient.

Fallback Strategies#

  • Tiered Models: when the primary model fails or exceeds latency budget, fall back to a faster or more conservative model.
  • Partial Fulfillment: deliver partial responses while queueing full resolution to avoid blocking user flow.
  • Human Escalation: escalate to human review for high-stakes decisions, preserving context and recommendation history.
  • Retrial and Randomization: rotate between equally capable models to avoid single-point failures and to gather comparative performance data.

Adaptive Retries#

When a response fails quality checks (toxicity, hallucination heuristics, blank outputs), the controller can retry with adjusted parameters—higher temperature moderation, revised prompts, or degraded but safe modes. Set retry budgets to prevent runaway costs.

Incident Handling#

Integrate routing with incident response. If evaluation detects a regression, the controller should route away automatically, notify operators, and log affected sessions for follow-up.

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