Activeloop

Activeloop builds Deeplake, a GPU-native database that stores vectors and tensors together for AI agents, RAG and model training. Around it sit Hivemind for shared agent memory and Refinery for continual learning, aimed at enterprise ML and agent teams.

Deeplake keeps data versioned and queryable, streams it to GPUs for fine-tuning and exposes a serverless Postgres interface. Case studies on the site cover chatting with X-ray images, faster data prep for multimedia, search over tens of millions of medical documents and robotics models.

Hivemind captures agent traces and turns solved tasks into skills shared across teams, while Refinery uses production feedback to optimize databases, generate kernels and tune physical AI policies. Deeplake has its own site at deeplake.ai.