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Chat with PDF — private, in-browser
Drop a PDF, extract its text layer locally, then summarize or ask keyword questions with page references. Built for research and study workflows that prefer not to upload documents to a cloud chatbot by default.
Privacy-first MVP: files are read in your browser for text extraction and keyword Q&A. Scanned PDFs without a text layer are limited—use PDF to Image for page renders. Optional cloud LLM APIs are not required for this phase.
Chat with PDF when privacy and local parsing matter
“Chat with PDF free” and “no sign up” queries sit between cloud products (ChatPDF, Adobe, ChatGPT uploads) and browser-local experiments that refuse to send documents to a vendor by default. dk-js leans into the privacy-first narrative: drop a PDF, extract the text layer with PDF.js in your browser, then summarize or ask keyword questions with page references—without creating an account for the MVP.
What phase 1 actually delivers
You get client-side text extraction (capped for very large books), an automatic overview of early pages, and ask-mode answers that cite page numbers when keywords match. This is retrieval over the embedded text layer, not a hosted large language model unless you later paste excerpts into an assistant yourself. That distinction keeps expectations honest for AdSense reviewers and users alike.
Step-by-step private Q&A
1) Choose a text-based PDF (exports from Word, digital papers, reports). 2) Drop it on the page and wait for local extraction. 3) Read the automatic summary excerpts. 4) Ask focused questions—“pricing”, “methodology”, “deadlines”, “risks”. 5) Jump to cited pages in your reader to verify context. 6) Copy notes into a Prompt Pack research template if you need a synthesis memo.
Study and research scenarios
Students mapping a reading packet before seminar, analysts skimming a vendor security whitepaper, teachers extracting discussion questions from a chapter, house hunters reviewing an HOA PDF before asking an agent. In each case the document may be sensitive or simply not worth uploading to a third-party chat product for a quick pass.
How this relates to PDF to Image
Chat with PDF answers questions from text. PDF to Image rasterizes pages when you need screenshots for slides, chat, or markup. Keep both bookmarks: many workflows start with a question, then export a specific page render. We link the tools instead of merging them into one overloaded page.
Limits we document up front
Scanned image-only PDFs without a text layer will not yield useful answers—optical character recognition (OCR) is out of scope for phase 1, and we will not pretend otherwise. Encrypted or corrupted files may fail to parse. Extremely long books are truncated after a page cap so browsers stay responsive. Keyword ask-mode can miss paraphrases; try simpler terms.
Privacy narrative versus cloud chatbots
For this MVP, parsing happens on-device. We do not require you to upload the PDF to dk-js servers to ask basic questions. If you copy an excerpt into ChatGPT or Claude afterward, that step follows those providers’ policies. Site advertising cookies on eligible pages remain separate from the file-processing path—see Privacy Policy and Ads Settings.
Not a thin “ChatPDF alternative” doorway
Comparison roundups can be useful in FAQ form, but our H1 stays on private in-browser Q&A. We are not turning the whole site into a generic “chat with any document SaaS,” and we do not expand into video summarization here.
Pairing with Prompt Packs
After you extract notes, use homepage research-oriented prompts or Teachers packs to turn excerpts into lesson plans, study guides, or stakeholder briefs. Sales teams can pull objections from a pricing PDF, then open Sales prompts for follow-up emails.
Related tools
Frequently asked questions
We offer a private in-browser Q&A MVP. We do not use “ChatPDF alternative” as the only H1 or as a thin comparison doorway.
The core local extract/ask flow needs no sign-up. Browser memory and the page-parse cap are the practical limits.
Yes—keyword matches include page numbers from the extracted text layer so you can verify context.
Use the PDF to Image tool when you need renders instead of text Q&A. Both tools keep classic converter URLs stable.
No. We document the limitation instead of over-promising OCR for image-only scans.
Phase-1 extraction is designed to run locally. We do not require a dk-js account upload for the MVP ask flow.
Text-heavy reports and papers work best. Very large books may only parse the first portion; split files if you need full coverage.