Respan Observability provides comprehensive LLM monitoring and debugging for AI applications in production. The platform tracks every prompt, completion, latency metric, cost, and quality signal across all LLM providers from a single dashboard, giving engineering teams full visibility into their AI stack.
The observability suite includes real-time tracing of LLM calls with detailed breakdowns of token usage, response times, and error rates. Teams can set up alerts for cost spikes, latency degradation, or quality drops, and drill into individual traces to debug issues. Built-in evaluation tools enable automated quality scoring of LLM outputs using custom rubrics or reference-based evaluation.
Prompt management features allow teams to version, test, and deploy prompts without code changes. A/B testing capabilities enable comparing model performance across different configurations, and semantic caching identifies repeated queries to reduce costs. The platform integrates with popular frameworks like LangChain, LlamaIndex, and the Vercel AI SDK.
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Respan Observability IS the monitoring and evaluation platform. It provides real-time tracing, cost analytics, prompt management, and quality evaluation for all LLM interactions across your AI stack.
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Last verified: February 28, 2026