Local PDF summarization · Page-cited output

You opened a 60-page PDF. Here's the 60-second version.

A summarizer built around the cognitive cost of long documents — research papers, contracts, transcripts, financial filings — distilled into structured key points with citations to the source pages.Less reading. Same understanding.

auto_awesomeOpen the summarizer play_arrowSee how it works

Browser-side parsing. Citations on every bullet. No file leaves your device.

Why most summarizers fall short

A summary you can't trust is worse than reading the original. Three failure modes show up over and over in the field — this tool is engineered against each.

Failure 1
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Generic LLM dump

The whole document gets stuffed into one prompt and the model returns an essay-shaped paragraph. No structure, no priorities, no skim path. You still have to read the summary linearly.

Failure 2
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Hallucinated citations

Bullets cite "page 47" when the relevant content is on page 12 — or worse, fabricate quotes that aren't in the source at all. Without verifiable references, every claim has to be re-read against the original.

Failure 3
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Slow upload roundtrips

The PDF gets sent to a server, queued, parsed remotely, then the summary streams back. For a 200 MB binder on a coffee-shop connection, you've waited a minute before a single token appears.

How the summarizer works

Four passes. The PDF stays on your device the entire time; only the extracted text segments are summarized.

01
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Parse locally

WebAssembly extracts the text layer page-by-page in your browser. Layout, headings, and pagination are preserved so citations stay accurate.

02
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Chunk by section

Headings, page breaks, and semantic boundaries split the document into sections. Each chunk carries its page range as metadata.

03
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Distill key points

Each section is reduced to its load-bearing claims. Long boilerplate compresses; substance survives. Page references travel with each bullet.

04
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Assemble TL;DR

Section summaries merge into a single ranked list of key points — copy-paste ready, with clickable citations back to the source pages.

When to reach for this tool

Long-form, dense, or technical PDFs where the cost of skimming is high and the cost of misreading is higher.

science

Research papers

Method, results, limitations — extracted in the order a reviewer reads. Citations point to the relevant section of the paper.

Academic
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Contracts & agreements

Term, fees, termination, indemnity, governing law. Pulled out as discrete bullets so you can spot the obligations that matter.

Legal
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Meeting transcripts

Decisions, action items, owner, deadline. Filler conversation drops away; the durable outcomes stay.

Operations
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Financial reports

10-Ks, earnings releases, annual reports — the figures that moved, the guidance that changed, the risks newly disclosed.

Finance

The old way vs. our way

Same input PDF. Two different paths to "now I get it."

Old way

Upload, wait, hope the summary holds up.
  • closeUpload your PDF to a stranger's server before anything happens
  • closeOne paragraph of prose — no skim path, no priorities
  • closeCitations either missing or fabricated; can't verify in seconds
  • close"Daily limit reached" after three documents
  • closeSign-up wall before the first summary renders

Our summarizer

Drop, distill, verify.
  • checkPDF parsed in your browser — the binary never leaves the page
  • checkStructured key-points extraction — ranked bullets, scannable
  • checkEvery bullet carries a page citation that links back to the source
  • checkLong-form mode for deeper passes; chat-with-PDF for follow-ups
  • checkNo upload, no signup gate, no daily summary cap

Need to drill deeper after the TL;DR? Open a chat session against the same PDF — questions get answered with the same page-citation discipline.

Three things this tool actually does

Verifiable claims only — features you can confirm in DevTools or against the source PDF.

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Local processing

PDF parsing and chunking run in WebAssembly inside your browser. The file binary never crosses the network.

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No file upload

Open DevTools → Network during a summary run. You will see no request body containing your PDF — only short text segments.

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Source-cited output

Each bullet links to the exact page or page range it came from, so every claim in the TL;DR is verifiable in two clicks.

The same browser-first model powers our other tools — translate a PDF without uploading it, compress a PDF locally, convert PDF to Word in-browser, or send confidential files via end-to-end encrypted transfer.

Questions about the summarizer

Edge cases, limits, and the things that usually go unsaid.

Does the summarizer work on scanned PDFs?
Only after OCR. A scanned PDF is a stack of images — there's no text layer to summarize until characters are recognized. Run the file through an in-browser OCR pass first, then the summarizer can extract key points. If the OCR confidence is low, the TL;DR will flag uncertain passages instead of inventing content.
How long can the input PDF be?
Practical ceiling is around 800 pages of dense text, or roughly 400,000 tokens, chunked and progressively distilled. Longer documents are split into sections, each summarized separately, then merged into a final TL;DR. Browser memory is the real limit — a modern laptop handles a 60-page report in seconds and a 600-page legal binder in under a minute.
Does it cite the source pages?
Yes. Every bullet in the TL;DR carries a page reference like p.12 or pp.34–37 pointing back to the passage that produced it. Click a citation to jump to the original page. This is what separates auto-summary from a hallucinated paraphrase — you can verify each claim in two seconds. For free-form follow-ups against the same PDF, switch to chat-with-PDF.
Does my file leave my browser?
PDF parsing, text extraction, and chunking happen entirely client-side via WebAssembly. The model call carries only the extracted text segments needed for summarization — your file binary never leaves the device. Open DevTools → Network during a run and you will see no PDF upload. Same model as our no-upload compressor and no-upload converter.
Why is the output sometimes shorter than I expected?
A good summary is bounded by signal density, not page count. A 200-page agreement with heavy boilerplate may compress to eight bullets because the unique substance is small. The summarizer favors brevity over padding — if you want more depth, switch to long-form mode or open a chat session against the document. Length-padding is what makes summaries unreadable.

Stop reading the whole thing. Read the TL;DR.

Drop a PDF, get a structured set of key points with page citations — in your browser, in seconds, without sending the file anywhere.

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