Evidently AI

What is Evidently AI?

Evidently AI is an open-source framework for evaluating, testing and monitoring AI systems, including LLM applications, RAG pipelines, AI agents and classic machine learning models. The library is licensed under Apache 2.0 and has over 7,500 GitHub stars and more than 40 million downloads.

Key capabilities of Evidently AI

• Automated evaluation: measures output quality, safety and reliability with shareable visual reports
• 100+ built-in metrics: covers hallucinations, factuality, PII detection, retrieval quality, toxicity and sentiment
• Custom evaluations: lets you define checks with any prompt or model
• Synthetic data: generates realistic, edge-case or adversarial test inputs
• Continuous monitoring: live dashboards that surface drift and regressions
• Data drift tests: test suites for tabular and ML model inputs

How Evidently AI works

You install the Python library, run evaluations on datasets or logged outputs, and get reports of metric results that can be shared or turned into pass/fail test suites. For production, results are sent to a monitoring dashboard so drift and regressions show up over time. LLM-based judges can be configured with your choice of model.

Who uses Evidently AI?

ML engineers, data scientists and AI product teams use it to test chatbots, RAG systems and agents before release and to monitor models afterward. The community numbers over 3,000 members.

Evidently AI pricing

The open-source library is free under Apache 2.0. The pricing page fetched for this profile did not list plan prices, so check the vendor for hosted cloud tiers.

Evidently AI alternatives

Hopsworks is a feature store and ML platform, ZenML is a pipeline orchestration framework, and Seldon focuses on model serving and monitoring. Evidently is narrower, centered on evaluation and observability.