Read 11 Activeloop reviews and testimonials from customers, explore 6 case studies and customer success stories, and watch customer videos to see why companies chose Activeloop as their undefined

Activeloop frees deep learning teams from building complex data infrastructure so they can develop AI products faster. 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.

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Customer Rating Review Scorebased on 639 reference ratings
4.8/5.0 (639)

11Testimonials

  • "I chose Deep Lake among other vector databases due to its open-source nature, easy setup process, and developer-friendly features. It seamlessly integrates with AWS S3, which I found cost-effective and familiar. Moreover, it included a multi-modality feature that enabled us to store our content as embeddings for further analysis - a vital feature significantly improving our AI assistant's responsiveness."

    Jean-Charles TouzalinFounder
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6 Case Studies

  • How Earthshot, an AgriTech powerhouse in environmental conservation space, 5x their speed with 4x less resources required

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Read Activeloop Reviews, Testimonials & Customer References from 11 real Activeloop customers.

Browse Activeloop Case Studies, Customer Success Stories, & Customer References from 6 businesses that use Activeloop.

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