DataFuel

About DataFuel

DataFuel turns whole websites and knowledge bases into LLM-ready data with a single query, which is a narrower promise than a general scraper and a more useful one for anybody building retrieval. The output is the point: clean Markdown structured for RAG, JSON filtered by an AI-generated or hand-written schema, plain text, or AI-enhanced HTML, so the result drops into a vector database without a normalisation step of your own. It crawls entire sites rather than single pages, which is what documentation ingestion and knowledge-base building actually require, and it handles authenticated content — internal wikis, gated docs, course material — with encrypted credential storage, a capability most scraping APIs simply do not offer. GPT-4-powered extraction pulls structured JSON against a predefined schema when you need fields rather than prose. Automated logins, automated retries and a crawler are on every plan, and Zapier and Make integrations mean it can sit inside an existing automation without custom glue. A browser demo runs two scrapes per visitor so you can see the Markdown a URL produces before signing up. Credits are counted as one per URL scraped, with AI-powered scraping or AI schema generation costing fifteen credits per URL, so the price of the expensive path is stated up front rather than discovered on the invoice.

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