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.

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.
Data Processing: Process digital human 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.