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Evidently

Monitor ML and LLM systems: drift, quality, and evals.

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About

Evidently is the open-source ML monitoring platform: detect data drift, track data quality, and evaluate both classical ML and LLM systems — with interactive reports and a monitoring UI. 8k stars, Apache-2.0, 823k PyPI downloads/month. It covers the 'is my model still behaving' layer that training tools ignore: reference-vs-production comparisons, test suites, and LLM-as-a-judge evals. The commercial Cloud gets the newest features first; the OSS core remains genuinely useful for drift and quality checks.

What it can do

  • **Drift detection**: data and prediction drift out of the box
  • **Data quality**: missing values, duplicates, schema checks
  • **LLM evals**: quality, safety, and relevance metrics
  • **Reports**: interactive HTML reports
  • **Monitoring UI**: track metrics over time

Setup

```bash

pip install evidently

```

```python

from evidently import Report

from evidently.presets import DataDriftPreset

report = Report([DataDriftPreset()])

my_eval = report.run(reference_data, current_data)

```

Docs: docs.evidentlyai.com.

Prerequisites

Python 3.9+. Reference and current datasets to compare.

Use cases

monitoringdrift detectiondata qualityLLM evals

Works with

customGeneric API

Trust score — 8/10

/10 trustVerified

Scored 8/10 (verified tier, metrics-v1). Evidence: 7,983 GitHub stars (log-scaled vs catalog peers); blended with ~823,148 monthly package downloads; last push 14d ago; 8 releases/12mo; 330 open issues. Manual review: ML/LLM monitoring (drift, data quality, evals), 8k stars, 823k PyPI/mo; Cloud gets newest features; crowded space. License: Apache-2.0.

★ 7,983 GitHub stars

How the trust score is built

Full methodology →
Adoption · stars/downloads, log-scaled vs peers
7.8/10
Maintenance · recency, releases, issue load
7.2/10
Openness · license + docs
10.0/10
Manual review · sanity read + red-flag check
8.0/10
  • · 7,983 GitHub stars (log-scaled vs catalog peers)
  • · blended with ~823,148 monthly package downloads
  • · last push 14d ago; 8 releases/12mo; 330 open issues
  • · manual review: ML/LLM monitoring (drift, data quality, evals), 8k stars, 823k PyPI/mo; Cloud gets newest features; crowded space

Sources

Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.