RAGFlow
AI searchAsk questions of your company documents and get answers with citations.
RAGFlow is built for teams whose knowledge sits in messy files: scanned PDFs, slide decks, spreadsheets and manuals. Its parser reads layout, tables and images, and every chunk it creates can be viewed and corrected before a chat assistant uses it. Answers come with references back to the source passages.
- Parse PDFs, Word, slides, spreadsheets, images and scans into chunks you can view and edit.
- Pick a chunking template that fits the document, such as manuals, papers, laws, slides or Q&A.
- Connect hosted models or local Ollama and vLLM models, and build agents on a visual canvas.
What people use it for
Build a searchable policy and manual library
Create a dataset, choose a parsing template such as Manual or Laws, and upload your PDFs and Word files. Open the Chunk page to check the results, then create a Chat that answers staff questions with citations.
Check why an answer came out wrong
Open the parsed file to see each chunk, add keywords or questions to the ones that matter, and edit text by hand. Run Retrieval testing with a sample question to confirm the right chunks now come back.
Run a support agent over product material
On the agent canvas, add a Categorize step to sort incoming questions, a Retrieval step to look up product documents, and an HTTP request to call your ticket system. Embed the finished agent in your website as a chat widget.