Evidently AI is an open-source framework for evaluating, testing, and monitoring AI systems, built to keep AI models and LLM-powered applications “safe, reliable and ready – on every update.” Its core evaluation methodology is LLM-as-a-Judge, supplemented by custom evaluations using any prompt, model, or rule.
Automated assessment covers hallucinations, factuality, and safety metrics through 100+ built-in evaluations – adherence to guidelines, PII detection, retrieval quality, toxicity, and more – with visual reports, synthetic data generation for edge-case and adversarial testing, and continuous monitoring dashboards tracking quality drift over time. It supports chatbots, RAG applications, AI agents, and traditional ML models alike.
Evidently AI targets AI teams from startups to enterprise – MLOps engineers, data scientists, and ML infrastructure teams – already used by organizations including DeepL, Wise, Plaid, and Databricks. It’s fully open-source under the Apache 2.0 license, with 7,500+ GitHub stars and 40M+ downloads.
