SEAR: Schema-Based Evaluation and Routing for LLM Gateways

📰 ArXiv cs.AI

SEAR is a schema-based evaluation and routing system for LLM gateways to assess production LLM responses and route requests across providers

advanced Published 31 Mar 2026
Action Steps
  1. Define an extensible relational schema to cover LLM evaluation signals
  2. Implement fine-grained quality signals for production LLM responses
  3. Develop operationally grounded decisions for routing requests across providers
  4. Evaluate and refine the SEAR system for multi-model, multi-provider LLM gateways
Who Needs to Know This

AI engineers and researchers on a team can benefit from SEAR to improve the quality and reliability of LLM gateways, while product managers can use it to optimize routing decisions

Key Insight

💡 SEAR provides a systematic approach to evaluating and routing LLM responses, enabling more reliable and efficient LLM gateways

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🚀 Introducing SEAR: a schema-based evaluation and routing system for LLM gateways #LLM #AI
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