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 717 reference ratings
4.8/5.0 (717)

11Testimonials

  • “As the datasets enlarge and become multi-modal, next-gen solutions built specifically to address those use cases, like Deep Lake, will help AI teams deliver models to production faster, and more efficiently.”

    Arijit BandyopadhyayCTO – Enterprise Analytics & AI, Head of Strategy – Enterprise & Cloud Group
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6 Case Studies

  • how Ubenwa, a growing force in sound-based infant medical diagnostics, 2x efficiency & improved scalability with streamable, standardized Deep Lake datasets

    Arsenii GorinLead ML Engineer
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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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