Neptune.ai
Free tierML experiment tracking and model registry for teams running production ML pipelines
Free tier available·Technical·API available
Key strengths
Comprehensive ML experiment tracking with rich metadata loggingScalable model registry for versioning and artifact managementFlexible Python SDK integrating with any ML frameworkTeam collaboration with shared dashboards and run comparisonsSupports large-scale hyperparameter search and reporting
Free tier + paid plans
Warsaw, Poland
Founded 2017
Self-hostable
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Neptune.ai provides a lightweight Python SDK that integrates with virtually any ML framework — including PyTorch, TensorFlow, Keras, and scikit-learn — to log metrics, hyperparameters, model weights, images, and custom metadata with minimal code changes. All run data is stored in a versioned, queryable metadata store accessible via the SDK or REST API. Neptune also offers a model registry for staging/production model lifecycle management, and supports on-premises or SaaS deployment. It is particularly well-suited for large-scale hyperparameter optimization workflows using tools like Optuna or Ray Tune.