Tensorlake is an AI-driven cloud platform designed to transform unstructured data into structured, ingestion-ready formats optimized for AI applications. It specializes in document ingestion and data orchestration, offering advanced capabilities to parse real-world documents with an understanding of human-like layouts. Tensorlake seamlessly converts files, including PDFs, images, handwritten notes, spreadsheets, and presentations, into structured JSON or markdown chunks, making them suitable for retrieval and analysis by large language models (LLMs).
The platform provides robust Document Ingestion APIs for parsing, structured data extraction, and classification. It supports a wide array of file types and ensures accuracy by preserving the original layout and reading order. Post-processing features like chunking further enhance the usability of extracted data, making it ideal for tasks like Retrieval-Augmented Generation (RAG) workflows and business process automation.
Tensorlake also offers Serverless Workflows, enabling users to build and deploy Python-based workflows for end-to-end data processing. These workflows are fully managed, scaling elastically to handle workloads ranging from a few documents to millions, without requiring external databases or map-reduce engines. The serverless architecture ensures high performance, with sub-millisecond latency and cost-efficient processing.
Security is a core focus, with features like role-based access control (RBAC), namespaces for precise data access, and detailed logging for compliance. These capabilities support seamless collaboration and ensure data protection.
Tensorlake bridges the gap between unstructured data and LLMs, empowering users to extract and process data at scale with unparalleled accuracy and efficiency.
