Neptune.ai - ML Metadata Storage

Basic Information

• Company/Brand: Neptune.ai (acquired by OpenAI)
• Founders: Piotr Niedźwiedź, Jakub Czakon
• Country/Region: Poland/USA
• Official Website: https://neptune.ai/
• GitHub: https://github.com/neptune-ai
• Type: ML Experiment Tracking and Metadata Storage Platform
• Founded: 2017
• Funding Status: Acquired by OpenAI in 2025, SaaS platform shut down in March 2026

Product Description

Neptune.ai was a hosted platform focused on ML experiment tracking and model management, known for structured metadata recording, model comparison, and team collaboration. The platform supported 25+ ML frameworks, offering a powerful UI and scalable storage for large-scale experiments. Acquired by OpenAI in 2025 to enhance visibility into model behavior and improve tools for researchers to track experiments. The SaaS platform was shut down in March 2026.

Core Features/Characteristics (Historical)

• Structured Experiment Tracking: Track hyperparameters, metrics, model artifacts, and code versions
• Flexible Logging System: From simple metrics to complex visualizations, model checkpoints, and dataset versions
• Model Comparison: Powerful experiment comparison and visualization interface
• 25+ Framework Support: PyTorch, TensorFlow, XGBoost, scikit-learn, etc.
• Team Collaboration: Multi-user experiment management and knowledge sharing
• Scalable Storage: Support for large-scale experiment data storage
• API Integration: Rich API and SDK support

Business Model (Historical)

• Free Tier: Unlimited experiment tracking for individual users, with limited features
• Team Tier: $58-$234/user/month
• Enterprise Tier: Custom pricing
• Note: SaaS platform shut down in March 2026

Current Status

• Acquired by OpenAI: Neptune's technology and team joined OpenAI
• SaaS Platform Shut Down: Service discontinued in March 2026
• Migration Recommended: Users need to migrate to alternatives like MLflow, W&B, etc.

Target Users (Historical)

• ML researchers and data scientists
• AI teams requiring experiment tracking
• Foundation model training teams
• Enterprises needing model management

Historical Competitive Advantages

• Focus on structured metadata management
• Intuitive and powerful experiment comparison UI
• Flexible logging and tracking system
• Broad ML framework support
• Scalable enterprise-grade storage

Comparison with Competitors (Historical Reference)

Alternative Recommendations

• MLflow: Open source and free, largest community
• Weights & Biases: Best commercial solution in terms of experience
• ClearML: Open source full-stack solution, low cost
• Comet ML: Commercial alternative with similar features

Relationship with OpenClaw Ecosystem

Neptune.ai has been acquired by OpenAI and its SaaS service has been shut down, making it unsuitable as a direct component of the OpenClaw ecosystem. However, its concepts and practices in ML metadata management are worth referencing. OpenClaw should consider using actively maintained alternatives like MLflow, W&B, or ClearML to implement experiment tracking and metadata management functionalities. Neptune's acquisition by OpenAI also highlights the strategic importance of ML observability in the AI field.