evidently
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
💡 Why It Matters
Evidently addresses the critical need for monitoring and evaluating machine learning models and data pipelines. It provides ML and AI teams with a comprehensive set of over 100 metrics to assess data quality and model performance, ensuring that systems remain reliable and effective. With a steady growth of 312 stars over 96 days, it demonstrates a stable community interest, indicating its maturity as a production-ready solution. However, it may not be the right choice for teams needing highly specialised observability features or those working with non-standard data formats.
🎯 When to Use
Evidently is a strong choice when teams require a robust open source tool for engineering teams to track data drift and model performance in real-time. Consider alternatives if your project demands specific integrations or features not supported by this framework.
👥 Team Fit & Use Cases
This tool is particularly beneficial for data scientists, machine learning engineers, and AI product managers who need to ensure the integrity of their models. It is commonly integrated into AI-powered applications, data validation systems, and data quality monitoring solutions.
🎭 Best For
🏷️ Topics & Ecosystem
📊 Activity
Latest commit: 2026-02-14. Over the past 97 days, this repository gained 312 stars (+4.6% growth). Activity data is based on daily RepoPi snapshots of the GitHub repository.