Activeloop offers Deep Lake, an AI-native database that connects unstructured data—audio, video, images, text, and embeddings—to machine learning models and large language models. The product is designed for enterprise use and supports on-premise deployment with an embedded architecture that can be set up in a few lines of code. Deep Lake is used by Fortune 500 companies in regulated sectors such as biopharma, MedTech, legal, and automotive to manage private data for GenAI without exposing it to external parties. The company is led by CEO Davit Buniatyan and intends to use the new funding to onboard additional enterprise customers and expand product adoption. Financially, Activeloop raised $11M in a Series A, bringing its total funding to about $20M. The round signals continued enterprise-focused growth rather than consumer expansion. Activeloop is building a database and open-source API designed to efficiently store and stream unstructured media data (video, audio, images) to AI models for computer vision, audio processing and NLP. The product converts media into mathematical representations, supports versioning, and can store repositories in systems like Amazon S3. The company is releasing an alpha of a commercial product that will add features such as SQL queries over streaming data on top of the open-source API. Activeloop grew out of founder Davit Buniatyan's research at Princeton and was part of Y Combinator's summer 2018 cohort. The company is pre-revenue but reports product traction in its community: 55 contributors, about 700 community members, and roughly 300,000 downloads of the program. The team has 15 employees and is hiring roughly half a dozen engineers as it builds the commercial offering.

Total raised

$16M

Funding rounds

2

Latest round

Series A

Latest activity

Mar 2024