Activeloop, the leading Database for AI company, has raised $11 million in Series A funding from Streamlined Ventures, Y Combinator, Samsung Next, Alumni Ventures, and Dispersion Capital. The round brings Activeloop's total funding to about $20 million.

Activeloop's Deep Lake seamlessly connects unstructured data-audio, video, images, text, and embeddings-to machine learning models, offering advanced storage and accurate retrieval for machine learning.

Deep Lake is a Database for AI powered by a unique storage format optimized for deep-learning and Large Language Model (LLM) based applications. It simplifies the deployment of enterprise-grade LLM-based products by offering storage for all data types (embeddings, audio, text, videos, images, pdfs, annotations, etc.), querying and vector search, data streaming while training models at scale, data versioning and lineage for all workloads, and integrations with popular tools such as LangChain, LlamaIndex, Weights & Biases, and many more. Deep Lake works with data of any size, it is serverless, and it enables you to store all of your data in one place. Deep Lake is used by Intel, Bayer Radiology, Matterport, Hercules.ai, Red Cross, Yale, & Oxford.