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Activeloop Raises $11M Series A and Brings Its Database for AI to Fortune 500 Companies

Insider Brief

  • Activeloop has secured $11 million in Series A funding, led by Streamlined Ventures and supported by Y Combinator, Samsung Next, Alumni Ventures, and Dispersion Capital, bringing its total funding to approximately $20 million.
  • The company’s product, Deep Lake, connects unstructured data types directly to machine learning models, enhancing storage and retrieval efficiency for enterprises in regulated sectors, including biopharma and automotive, and improving the productivity and cost-effectiveness of AI engineering teams.
  • The new funding will be used to onboard more enterprise customers, scale the engineering team, and further develop Activeloop’s capabilities in organizing and retrieving complex unstructured data for AI applications, while maintaining high security standards such as SOC-2 Type II compliance.

PRESS RELEASE — MOUNTAIN VIEW, Calif./March 26, 2024 /PRNewswire/ — 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 $20M.

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.

Activeloop’s enterprise-ready database is popular among Fortune 500s in regulated sectors like biopharma, MedTech, legal, and automotive. Innovative enterprises like Bayer Radiology and Matterport, among others, use Activeloop to train and fine-tune large language and deep learning models, while also leveraging its capabilities for storing and searching vast amounts of data. Activeloop’s offering enables multi-modal retrieval-augmented generation (RAG) with high accuracy and cost effectiveness.

“For customers across industries, Activeloop feels like a magic box that helps teams organize their unstructured complex data and efficiently retrieve it for AI,” said Davit Buniatyan, CEO of Activeloop. “With Deep Lake, enterprises can create AI applications that are more accurate, boost AI engineering teams’ productivity by up to 5x, and cost up to 75% less than market offerings,” concluded Buniatyan.

“It’s next-level. We’ve enabled a new human-machine interface that is natural to use and yields high-accuracy results for end-users,” said Steffen Vogler, Principal Imaging Technology Scientist, from Bayer Radiology.

Deep Lake also improves knowledge retrieval accuracy with LLMs by 22.5% on average. Its AI-native embedded architecture ensures easy on-premise setup in just a few lines of code, meeting top security standards like SOC-2 Type II. This makes it the preferred choice for enterprises seeking to manage their private data for GenAI without exposing it to external parties.

“Enterprises seek AI to unlock value from complex data, which is only possible with systems like Activeloop’s database for AI. Given their solid track record, we trust the team to execute their vision and are excited to invest again in this round,” said Ullas Naik, General Partner at Streamlined Ventures.

New capital will enable the onboarding of further enterprise customers, empowering anyone to organize complex unstructured data and retrieve knowledge with AI. The company will also scale its engineering team.

See the company’s full announcement here.

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James Dargan
About the author
James Dargan

James Dargan is a writer and researcher at The AI Insider. His focus is on the AI startup ecosystem and he writes articles on the space that have a tone accessible to the average reader.

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