Evidently AI / evidentlyai.com
Open source ML monitoring framework that tests, evaluates, and monitors machine learning models with pre-built reports for data quality, data drift, model performance, and LLM quality evaluation.
Pricing
Free
Free plan
Yes
Category
Developer Tools
Platforms
4
Free plan
Yes
API access
Yes
Open source
Yes
Platforms
4
Evidently AI is an open source Python library for ML model evaluation and monitoring — providing pre-built tests and visualisations for data quality, data drift, model performance, and, increasingly, LLM output quality. It's the most widely adopted open source tool in the ML monitoring space, used by data science teams who want monitoring capabilities without vendor lock-in.
Pre-built test suites for common ML monitoring scenarios — data quality tests, data drift tests, model performance tests — can be run in Jupyter notebooks or integrated into ML pipelines with a few lines of code. Reports provide visual HTML outputs that teams can share without separate dashboard infrastructure.
LLM evaluation added Evidently to the LLM quality monitoring space — providing pre-built evaluations for response relevance, factual accuracy, toxicity, and custom metric evaluation for LLM-generated text. As LLM deployment grows, ML teams familiar with Evidently extend the same monitoring framework from traditional ML to LLMs.
Evidently Cloud provides a managed dashboard layer for teams who want Evidently's open source capabilities with persistent monitoring without building their own infrastructure — bridging the open source library and commercial platform gap.
The open source approach means no vendor lock-in, full code customisation, and free access — making Evidently the default choice for teams starting ML monitoring and wanting to understand the fundamentals before committing to a commercial platform.
Evidently AI runs as ml platform software built around data and text workflows. Users typically start with a prompt, upload, or connected data source, and the underlying model handles the heavy lifting before returning a result you can refine or export. It's available on python, jupyter, and cli, with API access for teams that want to embed it into their own products.
The capabilities that matter most for teams evaluating Evidently AI.
Ready-to-run tests for data quality, data drift, and model performance that run in Python with a few lines of code — no custom metric development required to start monitoring.
Pre-built evaluations for LLM output quality (relevance, toxicity, factual accuracy) extending the same monitoring framework from traditional ML to LLM applications.
Visual HTML reports from monitoring runs shareable without separate dashboard infrastructure — enabling monitoring output sharing from Jupyter notebooks or CI/CD pipelines.
Open source is free. Evidently Cloud free tier available. Pro and Enterprise plans. Community-driven.
Model
Open Source
Starting price
Free
Free trial
No
Arize (rank 612) provides commercial ML observability with free tier. WhyLabs provides commercial ML monitoring. Fiddler AI (covered) provides ML observability with explainability. Great Expectations (mentioned earlier) provides data quality testing.
A side-by-side look at the closest alternative in this category.
Key facts about model providers, platforms, and team support.
Model Provider
Evidently AI
Platforms
Python, Jupyter, CLI, Web
Deployment
Open Source, SaaS
Integrations
MLflow, DVC, Airflow, Spark, API
Team Collaboration
No
Launch Year
2023
Compliance signals and data-handling notes as reported by the vendor.
Apache 2.0 open source licence. Evidently Cloud SOC 2 compliant. GDPR compliant. Data processing on customer or Evidently Cloud infrastructure.
Open source version runs entirely on customer infrastructure — no data sent externally. Evidently Cloud processes data on managed infrastructure. Open source is fully private by design.
Editorial Verdict
Evidently AI is the best open source ML monitoring framework for data science teams wanting free, customisable model monitoring, data drift detection, and LLM evaluation without vendor lock-in.
Last verified July 24, 2026.
Open source is free. Evidently Cloud free tier available. Pro and Enterprise plans. Community-driven.
Free plan (1 user, limited storage). Team $179/month. Enterprise custom.
Apache 2.0 open source licence. Evidently Cloud SOC 2 compliant. GDPR compliant. Data processing on customer or Evidently Cloud infrastructure.
SOC 2 Type II. ISO 27001. GDPR compliant. On-premise deployment option for data privacy. Enterprise data handling agreements.
Open source version runs entirely on customer infrastructure — no data sent externally. Evidently Cloud processes data on managed infrastructure. Open source is fully private by design.
Review Comet ML's data handling policy. Experiment data, metrics, and artefacts processed on Comet's infrastructure. On-premise deployment keeps data on customer infrastructure.
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