Entrovix AI

AI PDF Summarizer

Summarises a PDF with the page number attached to every point, so any claim you doubt takes seconds to check — and scanned files carrying no text layer are flagged.

Your document

Drop a PDF here

The text is read here in your browser, one page at a time.

Every point carries the page it came from, so the two or three that matter take seconds to check.

Summary

Your result appears here, with the page behind each point.

Why use it

Built to be genuinely useful

Every point cites a page

A summary you cannot check is worth little, so every line carries the page number it was drawn from.

Scanned PDFs are detected

A photographed page has no text layer at all — the tool says so rather than returning a confident summary of nothing.

Extraction runs page by page

Text is pulled out one page at a time, which is what makes the page number available to attach to each point.

Long documents stay navigable

A 200-page annual report becomes twelve points you can each trace back, rather than one paragraph you have to trust.

How it works

Three steps

  1. 1

    Upload the PDF and let the text come out page by page.

  2. 2

    Read the summary with the page number sitting beside each point.

  3. 3

    Open the pages behind the two or three points that matter.

Why an unchecked summary is the dangerous one

A summary is most useful for a document you have not read, which is exactly the situation in which you cannot tell a good summary from a wrong one. Most summarisers hand back a clean block of prose with nothing pointing back at the source. It reads well either way.

The failure is quiet. A ninety-page tender document might set the bid bond at 2 percent in one clause and 5 percent in an annexure, and a summary that picks the wrong figure reads exactly as confidently as one that picks the right figure. You have no way of noticing.

So every point here arrives with the page it came from. You are not being asked to trust the summary whole — you check the two or three points you will actually act on, and read the rest as orientation. Checking one page takes seconds; re-reading ninety does not.

What a scanned PDF actually contains

A PDF is a container, and two files that look identical on screen can hold completely different things. One holds text — characters, positions, fonts. The other holds a photograph of a page, which is what a phone scan, an office photocopier or an old court order usually produces. On screen they are indistinguishable.

Extraction on the second kind returns an empty string. Many summarisers never check for that — they pass the empty text along, and a model given nothing to work with writes a plausible paragraph about a document it has never seen. Nothing in the output tells you this has happened.

This tool counts what came out of each page and stops when there is nothing to summarise, telling you the file is a scan rather than inventing around it. It does not read the images itself. It points you at the AI OCR tool, which recognises the text and hands back a version this one can work from.

Where citations help and where they stop

Page numbers change how you read the output. Instead of accepting or rejecting the whole summary, you can treat each point as a claim with an address — the penalty clause on page 34, the revised fee on page 12 — and go straight there. That is a different kind of reading.

What a citation does not do is prove the point is right. It tells you where to look, and the extraction can attach a page correctly while the sentence built on top of it overstates or flattens what that page said. The check is still yours to make.

Use it where being roughly right is enough — deciding whether a 300-page report is worth your evening, or finding which section of a syllabus covers a topic. Where the number goes into a contract, a filing or an answer script, read the page. A summary is a reading aid.

FAQ

Questions people ask

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