How to prepare data from multiple sources for RAG systems?

Prepare data from multiple sources for RAG systems using Supametas.AI

This task can be performed using Supametas.AI

Unstructured data processing platform

Best product for this task

Supame

Supametas.AI

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Supametas.AI is a platform that transforms unstructured data into structured formats suitable for use in large language models (LLMs) and retrieval-augmented generation (RAG) systems. The platform is designed to simplify data collection, construction, and preprocessing for industry-specific datasets, making it easier for companies to bypass complex data cleaning processes. Users can convert data from multiple sources such as APIs, URLs, local files, images, audio, and video into JSON and Markdown formats, which are then seamlessly integrated into LLM RAG knowledge bases.

What to expect from an ideal product

  1. Pulls data from different places like websites, files, and media into one central spot for easy management
  2. Turns messy content from videos, audio files, and documents into clean, structured text that RAG systems can use
  3. Changes everything into JSON or Markdown format, making it ready to plug straight into language models
  4. Handles the dirty work of cleaning and organizing data from multiple sources, saving time on manual processing
  5. Creates industry-specific datasets by gathering and formatting information from various inputs without complicated setup

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