List of Activeloop Deep Lake Customers
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Since 2010, our global team of researchers has been studying Activeloop Deep Lake customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Activeloop Deep Lake for AI infrastructure from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Activeloop Deep Lake for AI infrastructure include: Bayer Vital Germany, a Germany based Healthcare organisation with 1500 employees and revenues of $600.0 million, Matterport, a United States based Professional Services organisation with 590 employees and revenues of $136.0 million, Ropers Majeski, a United States based Professional Services organisation with 120 employees and revenues of $45.0 million and many others.
Contact us if you need a completed and verified list of companies using Activeloop Deep Lake, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The Activeloop Deep Lake customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight | Insight Source |
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Bayer Vital Germany | Healthcare | 1500 | $600M | Germany | Activeloop | Activeloop Deep Lake | AI infrastructure | 2024 | n/a | In 2024, Bayer Vital Germany implemented Activeloop Deep Lake on its enterprise cloud to unify multimodal biomedical datasets and to support radiology AI workflows, Apps Category . The deployment targeted Bayer Radiology and was positioned to reduce developer data-preparation effort while enabling natural-language interaction with imaging assets. Activeloop Deep Lake was configured to centralize multimodal biomedical data, focusing on image indexing, vectorized retrieval, and dataset versioning to accelerate prototype iterations. Developers reported cutting an approximately 50% data-preparation burden down to a small fraction, and the implementation enabled a natural-language ‘‘chat with X rays’’ capability that leverages improved AI retrieval for medical imaging. The project was integrated in under two weeks into Bayer Radiology's cloud environment, aligning deployment with healthcare and radiology workflows and secure data handling practices. Operational scope centered on radiology development teams and prototyping pipelines, with governance oriented around enterprise cloud security and controlled access to imaging datasets. | |
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Matterport | Professional Services | 590 | $136M | United States | Activeloop | Activeloop Deep Lake | AI infrastructure | 2023 | n/a | In 2023, Matterport deployed Activeloop Deep Lake, Category: , to standardize and stream very large multimodal 3D and imagery datasets for a US based machine learning and vision initiative. Activeloop Deep Lake served as the central AI native dataset store for computer vision model training, enabling a consistent dataset interface across experimentation and training workflows. The implementation focused on multimodal data management and real time streaming capabilities, standardizing dataset schemas and enabling direct dataset consumption by training pipelines. Configuration emphasized dataset versioning, indexed storage for large 3D and imagery assets, and streaming endpoints to feed models during training and evaluation, with Activeloop Deep Lake providing the dataset orchestration layer. Operationally the rollout was scoped to US based ML and vision teams in R and D and engineering, impacting data preparation, model experimentation, and training operations. The system was integrated into existing model training workflows to deliver continuous dataset access and faster iteration, with Deep Lake acting as the single source of truth for multimodal training data. Governance and workflow changes centralized dataset management and reduced manual data preparation handoffs, supporting faster experiment cadence. The deployment cut training data preparation time by about 80 percent and reduced time to train from hours to seconds, with Deep Lake positioned as the authoritative dataset store for subsequent model development cycles. | |
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Ropers Majeski | Professional Services | 120 | $45M | United States | Activeloop | Activeloop Deep Lake | AI infrastructure | 2024 | n/a | In 2024 Ropers Majeski deployed Activeloop Deep Lake as the core storage and retrieval layer for a Hercules.ai solution developed in partnership with Intel to support legal and knowledge management processes in the United States, Category . The deployment focused on secure, enterprise grade storage of millions of sensitive legal documents and vector embeddings to enable high‑performance semantic retrieval and downstream RAG workflows. Activeloop Deep Lake was configured to persist document objects and embeddings at scale, with functional capabilities for semantic search indexing, embedding management, and programmatic retrieval. The implementation emphasized vector storage architecture and query orchestration, and included operational controls for ingestion pipelines, embedding lifecycle handling, and search scoring to support lawyer-facing knowledge workflows. The solution integrated Activeloop Deep Lake with the Hercules.ai application layer and associated embedding generation components provided by the implementation team and Intel partnership, preserving sensitive content within a secured data plane. Operational coverage targeted legal and knowledge management teams within Ropers Majeski across the United States, and the deployment model prioritized compliance controls and role based access controls to restrict retrieval and auditing to authorized legal staff. Governance was centered on access control policies, compliance logging, and workflow alignment for semantic search and retrieval augmented generation processes. Reported outcomes from the deployment include a 100x query speed improvement and an 18.5% increase in lawyer productivity as delivered by the Hercules.ai solution that leverages Activeloop Deep Lake. |
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