Tensorlake

Tensorlake

Tensorlake is an AI Data Cloud platform that transforms unstructured data into LLM-ready formats through robust document parsing, structured extraction, and serverless workflows.
https://tensorlake.ai/?ref=aipure
Tensorlake

Product Information

Updated:Jun 16, 2025

Tensorlake Monthly Traffic Trends

Tensorlake received 9.9k visits last month, demonstrating a Significant Growth of 326.8%. Based on our analysis, this trend aligns with typical market dynamics in the AI tools sector.
View history traffic

What is Tensorlake

Tensorlake is a comprehensive platform designed to bridge the gap between raw data and AI applications, particularly Large Language Models (LLMs). Founded by Diptanu Choudhury, it serves as an enterprise-grade solution for developers to process, transform, and prepare various types of unstructured data - including documents, images, presentations, videos, and audio - into structured formats that are optimized for AI applications. The platform combines document ingestion APIs with serverless workflow capabilities to create a seamless data processing pipeline.

Key Features of Tensorlake

Tensorlake is an AI Data Cloud platform that transforms unstructured data into LLM-ready formats through document parsing, structured extraction, and serverless workflows. It provides APIs and tools to process various file types, from PDFs to handwritten notes, while maintaining document context and relationships. The platform offers scalable infrastructure that can handle thousands of requests per day with automatic scaling capabilities and built-in security features.
Document Ingestion API: Parses and processes multiple file types while preserving reading order and layout, with built-in post-processing like chunking
Serverless Workflows: Python-based workflow APIs that automatically scale up or down based on processing needs, supporting parallel processing without requiring database or queue management
Secure Data Processing: Implements RBAC and namespaces for access control, detailed logging, and compliance features for enterprise-grade security
High Performance Processing: Handles 10,000 events per second with low latency (8e-6/sec) and can process over 100,000 documents per day per customer

Use Cases of Tensorlake

Document Processing Automation: Processing and extracting information from complex documents like property deeds, tax audit papers, and global trade paperwork
RAG Applications: Creating structured chunks optimized for Retrieval Augmented Generation (RAG) workflows from various data sources
Multilingual Document Processing: Handling mixed-language documents and converting them into structured formats for analysis

Pros

Highly scalable infrastructure that can handle large volumes of documents
Simple integration with Python-based APIs
Automatic parallel processing without complex infrastructure setup

Cons

Requires API key and authentication setup
May require technical expertise to implement custom workflows

How to Use Tensorlake

Install Tensorlake SDK: Install the Tensorlake SDK and Indexify CLI using pip or your preferred package manager
Get API Key: Sign up on Tensorlake platform and obtain your API key for authentication
Initialize Document AI: Import and initialize DocumentAI with your API key: from tensorlake.documentai import DocumentAI, ParsingOptions doc_ai = DocumentAI(api_key='your_api_key')
Upload Document: Upload your document using the upload() method: file_id = doc_ai.upload(path='/path/to/file.pdf')
Parse Document: Parse the uploaded document using parse() method with desired options: job_id = doc_ai.parse(file_id, options=ParsingOptions())
Retrieve Results: Get the parsed results using get_job(): data = doc_ai.get_job(job_id)
Build Workflow (Optional): Create custom workflows using @tensorlake_function() decorator to process data through multiple stages. Define input/output models using pydantic BaseModel
Deploy Workflow (Optional): Deploy your workflow as an HTTP endpoint that can be triggered via REST API calls. The workflow will automatically scale based on load
Monitor Results: Track your document processing jobs and workflow executions through Tensorlake's logging and monitoring capabilities

Tensorlake FAQs

Tensorlake is an AI Data Cloud platform that transforms unstructured data into LLM-ready formats for AI applications. It provides document parsing, structured extraction, and classification services through its APIs.

Analytics of Tensorlake Website

Tensorlake Traffic & Rankings
9.9K
Monthly Visits
#1557382
Global Rank
-
Category Rank
Traffic Trends: Mar 2025-May 2025
Tensorlake User Insights
00:02:30
Avg. Visit Duration
3.73
Pages Per Visit
35.22%
User Bounce Rate
Top Regions of Tensorlake
  1. US: 58.39%

  2. IN: 33.44%

  3. CA: 8.16%

  4. Others: NAN%

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