Opik by Comet
Trace, evaluate, and monitor LLM applications across the full development lifecycle
Opik by Comet is profiled here as a Prompt Management tool for engineering teams. Read about features, pricing, and how it compares to related options in the tools directory.
Description
Opik is the open-source LLM evaluation platform built by Comet, a New York-based ML platform company founded in 2017 by Gideon Mendels and Nimrod Lahav. Comet spent seven years solving experiment tracking and reproducibility for traditional ML before launching Opik in September 2024, when LLM teams were reproducing the same undocumented chaos that MLOps had already fixed for classical models. That heritage shapes Opik's design: it covers tracing, evaluation, production monitoring, and agent observability in one platform rather than treating them as separate concerns. Comet has raised $63M across its funding rounds and operates with 103 employees, distinguishing it from single-product startups in the same Testing category.
Key Capabilities
LLM and agent tracing: Deep instrumentation of LLM calls, RAG pipeline steps, tool invocations, and multi-agent workflows captures every decision point with full context, supporting frameworks including LangChain, LlamaIndex, AutoGen, Google ADK, and Flowise AI
LLM-as-judge and automated evaluation: Scored evaluation runs measure relevance, factuality, coherence, and hallucination across prompt versions and model configurations, with experiment management tracking results across iterations
Production monitoring with online evaluation rules: Live dashboards apply configurable evaluation rules to production traffic, alerting on quality regressions without waiting for offline test runs
CI/CD integration with test case storage: Evaluation suites run on every prompt or configuration change, with stored test cases enabling reproducible regression comparisons across deploys
Opik Agent Optimizer and Opik Guardrails: A production optimization layer that continuously improves agent behavior based on evaluation feedback, paired with guardrails that enforce quality and safety policies on live LLM outputs
Self-hosted deployment and MCP integration: Docker and Kubernetes deployment options keep evaluation data within a team's own infrastructure, and the opik-mcp repository extends Opik into MCP-compatible AI agent workflows
Alternative tools
- MLflow
Track experiments, manage models, and evaluate LLM applications across the full ML lifecycle
- Langtrace
Trace LLM application calls with OpenTelemetry and route data to any observability backend
- Orq.ai
European enterprise AI agent platform with EU AI Act compliance and agent runtime orchestration.
- Klu.ai
Collaborative prompt engineering platform with multi-LLM evaluation and fine-tuning.
- Humanloop
Prompt management and LLM evaluation platform — acqui-hired by Anthropic; platform ceased September 2025.
- Langflow
Visual drag-and-drop AI workflow builder with built-in MCP server deployment — now part of IBM.