evidently
An open-source Python framework to evaluate, test, and monitor ML and LLM systems with 100+ built-in metrics.
What is evidently?
Evidently is an open-source Python framework for ML and LLM observability. It helps data scientists and ML engineers evaluate, test, and monitor the performance and reliability of AI systems and data pipelines using a comprehensive suite of over 100 built-in metrics. It addresses the challenge of maintaining model quality and detecting issues like data drift in production.
Machine learning engineers, data scientists, and MLOps practitioners who need to validate, monitor, and debug ML models and LLM applications in development and production environments.
Developers choose Evidently for its extensive built-in metrics, flexibility to handle both tabular data and LLM evals, and its open architecture that supports everything from ad-hoc reports to continuous monitoring without vendor lock-in.
Overview
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.
Use Cases
Best For
- Detecting data drift and quality issues in production ML models
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