evidently
An open-source ML and LLM observability framework for evaluating, testing, and monitoring AI systems and data pipelines.
GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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Decision brief
Evidently is an open-source framework for evaluating, testing, and monitoring AI systems and data pipelines, offering over 100 metrics for assessing data drift, data quality, and model performance.
Good fit when
- Use Evidently when you need to evaluate and monitor generative AI systems, as it supports a wide range of metrics specifically tailored for these applications.
- Consider Evidently if your project involves tabular data, as it provides robust tools for assessing data drift and quality in such datasets.
Avoid when
- Avoid Evidently if your project requires real-time monitoring, as it is primarily designed for batch processing and post-deployment evaluation.
- Do not use Evidently if your team is not familiar with Jupyter Notebooks, as this is the primary interface for using the framework.
- Pricing:
- freemium - Evidently is free and open-source, but users may incur costs related to hosting and infrastructure when deploying it.
- Requirements:
- Min 2 GB RAM; Evidently can be installed via pip or conda, making it accessible to users with different package management preferences.
Observed Sep 18, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Very active (6d since push)
- As of Sep 18, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 18, 2026
- Security (OSV)
- No lockfile
- As of Sep 18, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
git clone https://github.com/evidentlyai/evidentlyHow it fits your stack(25)
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Evidently provides tools for assessing data drift, data quality, and model performance across various AI applications, including generative AI and tabular data.
Capability facts
- CLI
- CLI entrypoint
Source: pyproject.toml:[project.scripts] · Sep 18, 2026
- Languages
- jupyter notebook, python
Source: github.language+pyproject.toml · Sep 18, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Tags
README
:woman technologist: Install Evidently To install from PyPI: To install Evidently using the Conda installer, run:
For agents
This page has a .md twin and JSON over the API.