Evidently AI
An open-source tool providing evaluation, testing, and monitoring of ML models. Allows proactive performance optimization and includes over 100 metrics for data quality and model performance tracking.
Evidently AI is an open-source tool designed for data scientists and machine learning (ML) engineers to evaluate, test, and monitor ML models. It supports various types of data, including tabular, natural language processing (NLP), and large language models (LLM). The platform has gained significant traction, with over 3,700 GitHub stars and 3+ million downloads. With a community of over 2,000 members, Evidently offers the necessary tools to reliably run ML systems in production. The platform allows users to start with simple ad hoc checks and scale up to a complete monitoring platform, all within a single tool. Evidently offers an easy-to-use interface for building reports that provide a comprehensive view of data and ML model quality, enabling users to explore and debug their models efficiently. Additionally, users can test their pipelines before deployment, validate in production, and run checks for every model update, saving time on manual setup. Evidently enables users to monitor all aspects of their data, models, and test results. This proactive approach helps catch and resolve production model issues, ensure optimal performance, and continuously improve ML models. The platform offers over 100 metrics to understand, visualize, and track data quality, data drift, model performance, and more. The Evidently community is highly supportive, with data scientists and ML engineers providing positive feedback. Users praise Evidently for its promising model drift detection framework and its plug-and-play features for monitoring ML models. The platform is also commended for its simplicity, interactivity, and ease of implementation. To use Evidently, users can turn predictions into metrics and metrics into dashboards. They can customize their data collection preferences or use the default settings. Evidently provides a Python library for capturing metrics, summaries, and test results, allowing users to log data from anywhere in their pipeline, whether batch or real-time. The results can then be visualized on a monitoring dashboard, where data can be explored over time, views can be customized, and sharing with team members is made easy. Evidently offers flexibility in deployment options. It can be easily added to existing workflows, self-hosted for full privacy and control, or integrated into cloud platforms. Evidently Cloud platform is currently in development, and interested users can join the waitlist to get early access. The platform also provides resources such as blogs, tutorials, and guides to support users in utilizing the tool effectively. In summary, Evidently AI is an open-source ML monitoring and observability tool that caters to the needs of data scientists and ML engineers. With its comprehensive range of features, including evaluation, testing, and monitoring of ML models, the platform ensures the reliable deployment of ML systems in production. The positive feedback from the community, along with its broad user base, demonstrates Evidently's efficacy and ease of use. Whether users require data quality monitoring, model performance tracking, or data drift detection, Evidently provides the necessary tools and support.