Activeloop

About Activeloop

Activeloop provides infrastructure for continual learning based on observing production traces, storing them as shared memory, generating improvements, and verifying them with benchmarks and regression checks before release.

Its stack includes Deeplake for versioned, queryable, GPU-native agent data, Hivemind for converting agent trajectories into shared team skills, and Refinery for producing updates from feedback, including database optimization, kernel generation, and physical AI policy optimization.

Key features

• Vector and tensor storage in one store
• GPU streaming to fine-tuning workflows
• Serverless Postgres interface for queries
• Capture agent trajectories as shared team memory
• Distribute skills across teams and organization
• Verify improvements with benchmarks and regression checks

Activeloop at a glance