Top AI tools for # experiment tracking

Determined AI is an open-source deep learning platform that streamlines model training, distributed computing, and GPU resource management. It enables teams to train models faster while optimizing hardware utilization and experiment tracking.

• Contact for Pricing

MLflow is an open-source, end-to-end MLOps platform for building better models and generative AI apps. It simplifies complex ML and generative AI projects, offering comprehensive management from development to production.

• Free

Metaflow is an open-source framework that simplifies the building and management of machine learning, AI, and data science projects. It provides tools for versioning, orchestration, and scaling compute resources.

• Free

MLtraq is an open-source Python library for designing, executing, tracking, and sharing Machine Learning and AI experiments efficiently. It enables collaboration and reproducibility through SQL database integration.

• Free

Valohai is an MLOps platform that streamlines complex machine learning workflows with CI/CD capabilities and pipeline automation, supporting on-premises and any-cloud environments.

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Neptune is a scalable experiment tracker designed for monitoring, debugging, and visualizing thousands of per-layer metrics in foundation model training.

• Freemium
• From 50$

Picsellia is an MLOps platform designed specifically for Computer Vision, enabling teams to build, train, monitor, and improve their applications.

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Aim is an open-source, self-hosted AI metadata tracking tool that enables teams to log, compare, and analyze AI experiments, prompts, and other metadata through an intuitive UI and programmatic SDK.

• Freemium
• From 11$

Parea is a platform for testing, evaluating, and monitoring Large Language Model (LLM) applications, helping teams track experiments, collect human feedback, and deploy prompts confidently.

• Freemium
• From 150$

Labtools.AI is an AI-powered platform for scientific labs, enabling inventory forecasting, machine learning model training, and seamless integration with ELNs/LIMs without coding.

• Paid