Supametas.AI is an unstructured data ETL platform designed to simplify the process of converting various data formats into structured data suitable for LLM RAG (Retrieval-Augmented Generation) applications. It caters to enterprises looking to efficiently collect, construct, and preprocess industry-specific datasets for integration into LLM knowledge bases.
Key Features:
- Versatile Data Collection: Supports data ingestion from multiple sources, including APIs, web pages, local files (docx, pdf, txt, md, json), images (jpg, png), audio (mp3), and video (mov, mp4, mpv).
- Standardized Output: Extracts data into standard JSON and Markdown formats, ensuring compatibility with various LLM frameworks.
- LLM RAG Integration: Seamlessly integrates with LLM RAG knowledge bases, including OpenAI Storage and Dify Datasets, with API support for custom integrations.
- User-Friendly Interface: Offers a zero-threshold, out-of-the-box experience, enabling quick creation of industry datasets.
- Data Privacy: Provides options for both SaaS and private Docker deployment to address enterprise data privacy needs.
Use Cases:
- Knowledge Base Creation: Rapidly build and maintain LLM knowledge bases with structured data extracted from diverse sources.
- Data Preprocessing: Streamline data preprocessing pipelines for LLM applications, reducing manual effort and improving data quality.
- Digital Avatar Data Processing: Process digital human avatar data for use in AI applications.
- Content Transformation: Transform raw data into desired content formats, boosting productivity and efficiency.
- Podcast/Video Data Integration: Convert podcast audio and video data into LLM knowledge bases.
