Evidently AI

Founded 2020

Test, evaluate, and monitor machine learning models and large language model applications

Pricing model

Free Tier

Rating

★ People love it

Time to value

Quick Setup (< 1 hour)

You can use Evidently AI to evaluate, test, and monitor machine learning models and language model applications throughout development and production. The framework provides automated evaluations for tracking response quality, detecting hallucinations, and spotting sensitive data leaks like PII. It generates visual reports and dashboard metrics to catch data drift and model degradation early. You can also generate synthetic test prompts, run continuous checks on retrieval-augmented generation systems, and configure over a hundred custom tests to verify that models follow strict format and safety rules.

What Evidently AI does

Run automated quality tests on language model responsesGenerate synthetic adversarial prompts for stress testingMonitor data distribution shifts between training and live inferenceDetect leaked personal information in model outputsTrack retrieval quality metrics across RAG pipelinesInspect visual drift reports inside CI/CD pipelinesCreate custom rule-based and model-based evaluation metricsAutomated evaluations to assess model output quality and safetyBuilt-in detection for hallucinations, toxicity, and sensitive personal informationReal-time tracking of data drift and feature distribution changesOver 100 preset evaluation metrics and tests for predictive and generative modelsSynthetic input generation to test adversarial prompts and edge casesShareable visual dashboards for monitoring production performanceOpen-source framework released under the Apache 2.0 license