Activeloop

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.

Case Studies

Showing 6 Activeloop Customer Success Stories

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How AskRoger Built an AI Personal Assistant for Any Content

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

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IntelinAir faster AgriTech with aerial machine learning data pipelines

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How Sweep Tackled Sync & Indexing Issues With Deep Lake To Create A Performant AI-Powered Junior Dev That Fixes Bugs & Ships New Features on GitHub

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How Tiny Mile, Manot, & Activeloop Increased Accuracy, Reduced ML Retraining Costs, & Streamlined Robot Delivery with Data-Centric AI

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

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