Activeloop frees deep learning teams from building complex data infrastructure so they can develop AI products faster
Deep Lake open source for researchers & nascent teamsActiveloop automatically connects unstructured data like audio, video, image and point cloud data to machine learning models. Deep Lake open-source enables data streaming, scalable machine learning pipelines, and dataset version control for distributed workloads. You may also access one of 200+ machine learning datasets like MNIST, COCO, CIFAR, ImageNet or GTZAN in Deep Lake format, curated by our community. Learn more about Deep Lake open source by reading Deep Lake documentation, Deep Lake academic paper, or Deep Lake whitepaper.
Deep Lake for emerging startups & enterprisesBuild a solid data foundation for your ML workflows with Deep Lake. Query, version-control, visualize, & stream your datasets to ML models real-time. Activeloop’s stack is used by teams at Google, Intel, Waymo, and Red Cross to break down data silos, improve operational efficiency, & reduce costs.
Shaping the future of data is hard
So we've built an all-star team
Backed by world-class investors
Meet the leadership team
We believe that the future of ML is data-centric. Good data is essential for great models, and current methods of managing unstructured data for ML are simply not enough. Our team got together to make open, unified and optimized data for ML available to everyone - from students and researchers to startups and large enterprises.
We believe that actively learning from feedback, always putting the users first and being unafraid to achieve bold goals in times of uncertainty will enable us to shape the future of data.
Just look at these
- Davit BuniatyanCEO
- Ivo StranicHead of Product
- Tatevik HakobyanVP of Engineering
- Mikayel HarutyunyanCMO