Tensorlake Cloud is a platform for developers to get enterprise data ready for RAG systems, agentic applications, and automation pipelines. Use the Document Ingestion API to parse useful data out of documents, and the Workflows API to build and run end-to-end transformation and enrichment pipelines.

Introduction

Learn about Tensorlake Cloud and how to get started

Use Cases

Learn about the Use Cases for Tensorlake Cloud

Getting Started

Get started with Document Ingestion and parse your first document.

Try the Playground

Start parsing documents and extracting structured data without writing any code

Community

Get help and connect with other users in our community on Slack, GitHub, and social media.

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Introduction

Tensorlake is a developer platform for parsing and orchestrating structured data from complex documents including contracts, forms, PDFs, emails, and images.

Whether you’re building a RAG system, an agentic app, or an automation pipeline, Tensorlake gives you tools to:

  • Extract: Schema-driven parsing to get structured data from messy files
  • Enrich: Detect signatures, strikethroughs, or classify pages
  • Orchestrate: Trigger workflows and route logic based on extracted signals

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Key Features

  • Schema-first structured extraction — define what you want, get clean JSON back
  • Document chunking — split documents into smaller pieces for RAG and LLMs
  • Signature & strikethrough detection — turn visual cues into usable flags
  • Form and table parsing — with bounding boxes and layout information

Choose your interface

  • Playground — no-code interface to test and explore document parsing
  • Python SDK — build custom document ingestion and transformation workflows
  • Workflows API — run end-to-end pipelines for chunking, summarization, and enrichment

Enterprise support at scale

  • Fully managed infrastructure — no need to build or maintain distributed systems
  • Zero-cost scaling — scale down to zero when not in use, pay only for active processing

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Quick Start

Choose your path:

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Community

Need help? Have a feature suggestion? Join the Tensorlake community: