Entrovix AI

Ask Questions From a PDF

Find the answer inside a document and read it in the document's own words — quoted with its position, never paraphrased.

Runs in your browser — nothing is uploaded

PDF to search

Drop a PDF here

Nothing is uploaded — the text is read on your device.

Your file never leaves this device. The whole operation runs in your browser — nothing is uploaded, queued on a server, or deleted later, because nothing was ever sent.

Passages found

Ask a question about the document

It quotes your document — it does not paraphrase it

Answers are the actual sentences from your file, ranked by relevance, with their position. Nothing is generated, so nothing can be invented: you read the source text and judge it yourself. For a contract or a policy that is the only kind of answer worth having.

No account, no API, no upload

Ranking uses term-frequency weighting computed in your browser. There is no model behind this and no request leaves the page, which is why it works on a document you would never paste into a chatbot.
Why use it

Built to be genuinely useful

Quotes, never paraphrases

Answers are the actual sentences from your file, so you can judge them against the source.

No model, no upload

Ranking is computed in your browser. Nothing is sent anywhere.

Your file never leaves the device

The conversion happens in your browser. Nothing is uploaded, so nothing has to be trusted or deleted later.

Free, no sign-up, no watermark

No account, no page cap, and no badge stamped on the output.

How it works

Three steps

  1. 1

    Drop in the PDF.

  2. 2

    Ask your question in plain language.

  3. 3

    Read the passages it found, ranked by relevance.

Retrieval, not generation

A chatbot given your document will answer in fluent prose that may or may not reflect what the document says. When the question is 'what is my notice period', a confident wrong answer is worse than no answer.

This retrieves. It finds the sentences most relevant to your question and shows them as they appear, so the answer and its evidence are the same thing.

The trade is real: you get passages rather than a tidy sentence, and you have to read them. For anything consequential, that is the better deal.

How relevance is judged

Words are weighted by how rare they are in the document. A question about 'warranty' is answered by the sentences containing 'warranty', not by the many sentences containing 'the'.

Sentences next to a strong match get a small boost, because the sentence containing the answer is often beside the one containing the keyword.

If nothing matches

Use the words the document would use. A contract says termination where you would say quitting; a policy says excess where you would say deductible.

This matches words rather than meaning — the honest limit of doing it without a model, and the reason it also works on a document you would never paste into a chatbot.

FAQ

Questions people ask

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