Activeloop Integrations

Deeplake is an AI data runtime and GPU database built for teams developing agents, RAG systems, multimodal applications, robotics workflows, and generative media products. It is designed to solve the gap between GPU-powered AI models and CPU-bound data systems by keeping data closer to where AI workloads execute. The platform supports serverless Postgres, vector search, multimodal data storage, analytical workloads, and AI-optimized data lake functionality. Deeplake helps agents remember, retrieve, and act in fast cycles, making it useful for systems that need repeated context retrieval across long-running tasks. It can manage complex data such as video, images, point clouds, sensors, PDFs, audio, embeddings, model weights, and structured records. Developers can use familiar database concepts while gaining support for GPU-speed retrieval and scalable AI data operations. The platform is positioned for production-grade AI use cases where agents may generate databases, query thousands of times, and require faster memory access. Deeplake also supports private deployment patterns, including VPC environments, so organizations can keep sensitive data within their own infrastructure. With open-source adoption, enterprise security credentials, and a focus on agentic workloads, Deeplake helps AI teams build faster and more efficient data systems.