Tensorlake is an AI-powered data cloud designed to reliably transform unstructured data into formats ready for AI applications. It offers document ingestion APIs and serverless workflows to streamline data processing for LLMs.
Key Features:
- Document Ingestion API: Parses various file types (PDFs, handwritten notes, spreadsheets) while preserving layout and reading order.
- Serverless Workflows: Build and deploy Python-based workflows for data processing that scale automatically.
- Structured Extraction and Classification: Extracts structured data from documents and classifies them.
- RAG Optimization: Produces structured chunks optimized for Retrieval-Augmented Generation (RAG) workflows.
- Scalability: Processes millions of documents with high accuracy and cost-effectiveness.
- Secure by Design: Offers RBAC and namespaces for access control and data protection.
Use Cases:
- RAG (Retrieval-Augmented Generation): Preparing data for question answering systems.
- Business Process Automation: Automating data extraction from documents for various business processes.
- LLM Integration: Providing structured data to Large Language Models for analysis and generation.
- Data Transformation: Converting documents, images, and slides into structured JSON or markdown.
