// Trace & monitor
evidentlyv0.7.23
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
Open source Maintained For developers
IN ONE PARAGRAPH
evidently is evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
Good for: Developers and teams who want to trace & monitor.
01How to start
- 1Read the official quick-start (link above).
- 2Install from the official package registry:
pip install evidently - 3Try it on a small example before wiring it into a project.
02Alternatives & comparison
Compare side by side → mlflow The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data. ★ 28k opik Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards. ★ 23k openllmetry Open-source observability for your GenAI or LLM application, based on OpenTelemetry ★ 7.5k wandb The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production. ★ 11k langfuse 🪢 Open source agent evals & observability: Trace, evaluate, and improve LLM applications with one open platform. ★ 36k