Openlayer LLM Observability

Openlayer LLM Observability is a monitoring and tracing platform designed to provide visibility into large language model (LLM) pipelines running in production environments. Core capabilities include: - Pipeline tracing: Tracks every step of an LLM workflow, from initial prompts through intermediate tool calls and final model responses - Live system monitoring: Continuously runs safety and performance tests on live requests, covering prompt injection attempts, toxic output, and data leakage - Alerting: Sends real-time notifications when issues are detected, including latency spikes, hallucinations, or inappropriate content - Cost and latency tracking: Monitors token-level usage, dollar spend, and response times to help identify bottlenecks and expensive operations The platform is designed to support common GenAI architectures including: - Retrieval-Augmented Generation (RAG) systems - Multi-step agentic workflows - Tool-calling systems - Internal copilots Users can set custom thresholds and alerts based on performance and efficiency metrics. The instrumentation is designed to be lightweight, requiring minimal code changes to integrate into existing pipelines. Openlayer positions the product as part of a broader AI governance and observability platform, recognized in the 2026 Gartner Market Guide for AI Evaluation and Observability.