End-to-end knowledge base data processing solution
Traditional knowledge base construction needs to go through a four-step process of data collection → cleaning → annotation → format conversion, Supametas.AI realizes a leap in efficiency in the following ways:
- Omni-Channel CaptureSynchronized processing of multiple sources of data such as web pages/internal documents/meeting recordings, etc., with support for automatic crawling and updating at regular intervals (e.g., setting up a daily synchronization of regulatory websites).
- batch automationStructured output: 50 pages of PDF or 2 hours of audio can be completed in 30 minutes, more than 200 times faster than manual processing
- one-click integration: Built-in Dify/OpenAI and other platform connectors, automatically matching the schema requirements of the target knowledge base when exporting.
Best practices are: 1) Create "Financial Regulations" dataset 2) Add SEC website URL and local PDF manual 3) Set up weekly crawl updates 4) Check "Generate summary" and "Keyword tagging" options when exporting 5) Connect to corporate GPTs knowledge base. "5) Directly connect to the corporate GPTs knowledge base.
This answer comes from the articleSupametas.AI: Extracting Unstructured Data into LLM Highly Available DataThe
May not be reproduced without permission:AI productivity tools " How to optimize the efficiency of data preparation in building an enterprise knowledge base?
English 
简体中文 
日本語 
Deutsch 
Português do Brasil