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Respan is an LLM observability platform designed for production AI agents, providing proactive monitoring and evaluation to help teams trace behavior and implement improvements.
It captures full execution traces, including messages, tool calls, routing decisions, memory, environment state, and outcomes, enabling deep visibility into AI agent performance.[1][8] Respan automates workflow-level evaluations that trigger on changes to prompts, workflows, routing logic, models, or production behavior, turning observability data into actionable insights on regressions and fixes.[1]
The platform features an AI evaluation agent that analyzes failures, localizes root causes, recommends new evaluations, and intelligently samples production traffic for review, making evaluation a continuous process.[1] Teams use Respan to monitor high-volume AI applications, such as voice agents handling millions of calls, with support for rich metadata, threads, and exports.[2]
Built for production-scale AI observability, Respan processes billions of logs and trillions of tokens monthly, assisting teams in maintaining control over agent reliability and iteration.[1]
Website: respan.ai
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