This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
Most PDF-to-text tools just extract text. But when you feed that into an LLM or vector DB, tables break, scans become unreadable, and headers repeat in every chunk. RAGCheck doesn't just convert — it diagnoses. Get a RAG Readiness Score (0-100) with actionable recommendations. Download clean Markdown, structured JSON, and pre-chunked text optimized for embeddings. Free tier: 3 conversions/day. No signup required.
Hey PH! I built this after spending 2 days trying to install Docling on my VPS. I just wanted to convert 50 PDF manuals for my LangChain bot.
Most PDF converters just extract text. But when you feed that into an LLM, tables break, scans become unreadable, and headers pollute every chunk.
RAGCheck doesn't just convert. It diagnoses:
- RAG Readiness Score (0-100)
- Extractability, structure quality, table quality
- Scan ratio, noise level, chunkability
- Specific recommendations
Free for up to 10 pages. Built with FastAPI + Next.js on a $5 VPS.
Would love feedback from anyone building RAG pipelines!
Update: already seeing first uploads from PH traffic! Working on batch upload for Pro tier based on early feedback. Thanks for checking it out 🙏
About RAGCheck on Product Hunt
“Prepare PDFs for AI with RAG Readiness Score”
RAGCheck was submitted on Product Hunt and earned 3 upvotes and 2 comments, placing #118 on the daily leaderboard. Most PDF-to-text tools just extract text. But when you feed that into an LLM or vector DB, tables break, scans become unreadable, and headers repeat in every chunk. RAGCheck doesn't just convert — it diagnoses. Get a RAG Readiness Score (0-100) with actionable recommendations. Download clean Markdown, structured JSON, and pre-chunked text optimized for embeddings. Free tier: 3 conversions/day. No signup required.
RAGCheck was featured in Productivity (653.9k followers), Developer Tools (514k followers), Artificial Intelligence (471.1k followers) and GitHub (41.3k followers) on Product Hunt. Together, these topics include over 334.9k products, making this a competitive space to launch in.
Who hunted RAGCheck?
RAGCheck was hunted by Dmitry Perch. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how RAGCheck stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Dmitry Perch