
Activeloop
Database for AI
About Activeloop
We provide a simple API for creating, storing, versioning, and collaborating on multi-modal AI datasets of any size. With Activeloop's open-core stack, you can rapidly transform and stream data while training models at scale. Deep Lake powers foundational model training by acting as a vector database with significant benefits, such as (1) the ability to use multi-modal datasets to fine-tune your own LLM models, (2) storing both the embeddings and the original data with automatic version control, so no embedding re-computation is needed (3) truly serverless service with no vendor lock-in. How cool is that? GitHub loves us - we're one of the fastest-growing libraries there, and we're used by little-known companies like Google, Waymo, and Intel. No big deal. Our founding team hails from places like Princeton, Stanford, Google, and Tesla, and we're backed by Y Combinator & other Silicon Valley heavyweights. Activeloop is hiring, and we want you! Check out our open roles on our YC page and join the fun. 10-min demo: https://activeloop.wistia.com/medias/aibvo0dst2 Whitepaper: https://www.deeplake.ai/whitepaper
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Who founded Activeloop?
Activeloop was founded by Davit Buniatyan, Mikayel Harut, Sasun Hambardzumyan, Emanuele, Ashot Shakhkyan, Azat Manukyan, Levon Ghukasyan, Aram Zaqaryan, Vlad Babayan, Artyom Gishyan, Mikayel Harutyunyan, Vahan, Levon Ohanyan.