DataFuel API scrapes entire websites and knowledge bases in a single query. Get clean, markdown-structured web data instantly for your RAG systems and AI models. No complex scraping code needed.
🚀 Scrape entire websites or knowledge bases in one query—no need for custom scripts.
📝 Markdown-structured data—perfect for RAG, saving GPT-4 costs and improving accuracy.
🔒 Scrape behind logins—access data from password-protected pages effortlessly.
📦 JSON output—extract emails, names, addresses, training data, and more.
⛏️ No proxy or retry headaches—let us handle the hard stuff.
🎁 Free trial—your first 20 URLs are on us!
📊 RAG-Ready Data: Turn websites into clean datasets for retrieval-augmented generation (RAG).
🤖 Training Data: Automate high-quality dataset collection for fine-tuning models.
📚 Knowledge Bases: Build rich knowledge sources from the web for better AI reasoning.
📰 AI Updates: Track news, research, and docs to stay on top of AI trends.
🧪 Model Testing: Collect diverse real-world data for LLM evaluation.
📄 Tech Docs: Scrape and organize API and technical documentation for AI use.
Hey Fazier Community! I’m Sacha, the maker of DataFuel.dev. DataFuel is an API that helps you turn entire websites into LLM-ready data in a single query. No proxies, no retries, no complex scraping code—just clean, markdown-structured data instantly for your RAG systems and AI models. The idea came from my own experience while building ChatNode, an AI chatbot builder. I struggled to scrape entire websites reliably to train chatbots using retrieval-augmented generation (RAG). Managing proxies, handling retries, and cleaning up messy outputs was a nightmare. I built DataFuel to solve these problems and help others get web data faster, easier, and without the headaches. Here are some of my favorite features: 🚀 Scrape entire websites or knowledge bases in one query—no need for custom scripts. 📝 Markdown-structured data—perfect for RAG, saving GPT-4 costs and improving accuracy. 🔒 Scrape behind logins—access data from password-protected pages effortlessly. 📦 JSON output—extract emails, names, addresses, training data, and more. ⛏️ No proxy or retry headaches—let us handle the hard stuff. 🎁 Free trial—your first 20 URLs are on us! 💥 Launch special: Get 30% OFF for the first 3 months! I’m so excited to share this with the Product Hunt community. Whether you’re training chatbots, building RAG systems, or need clean web data for your project, I’d love for you to give it a try. Check out DataFuel.dev and let me know what you think! Ask me anything here—I’d love to hear your thoughts and answer your questions. 🚀
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Hey Fazier Community! I’m Sacha, the maker of DataFuel.dev. DataFuel is an API that helps you turn entire websites into LLM-ready data in a single query. No proxies, no retries, no complex scraping code—just clean, markdown-structured data instantly for your RAG systems and AI models. The idea came from my own experience while building ChatNode, an AI chatbot builder. I struggled to scrape entire websites reliably to train chatbots using retrieval-augmented generation (RAG). Managing proxies, handling retries, and cleaning up messy outputs was a nightmare. I built DataFuel to solve these problems and help others get web data faster, easier, and without the headaches. Here are some of my favorite features: 🚀 Scrape entire websites or knowledge bases in one query—no need for custom scripts. 📝 Markdown-structured data—perfect for RAG, saving GPT-4 costs and improving accuracy. 🔒 Scrape behind logins—access data from password-protected pages effortlessly. 📦 JSON output—extract emails, names, addresses, training data, and more. ⛏️ No proxy or retry headaches—let us handle the hard stuff. 🎁 Free trial—your first 20 URLs are on us! 💥 Launch special: Get 30% OFF for the first 3 months! I’m so excited to share this with the Product Hunt community. Whether you’re training chatbots, building RAG systems, or need clean web data for your project, I’d love for you to give it a try. Check out DataFuel.dev and let me know what you think! Ask me anything here—I’d love to hear your thoughts and answer your questions. 🚀