Summarizer
Summarize a document with AI, properly.
Upload a report, paper, or whitepaper and get a written summary that leads with the finding — not the first page, not a keyword extract. Free with an account.
- A language model reads the whole document, not a sample of it.
- Instructed to copy every figure exactly and keep hedged claims hedged.
- Returns prose plus discrete key points, so you can use either.
What this actually does
Your file is extracted server-side using the same parser our video pipeline runs, then a language model reads the extracted text and writes a summary. It is abstractive: the model writes new sentences in plain language rather than pulling quotes out of the original.
It is told to lead with the most important finding rather than with background, because documents build to their conclusion and a summary that does the same is no faster to read than the document.
- Three depths: brief, standard, and detailed.
- Key points come back as discrete standalone sentences.
- Key terms show what the document keeps returning to.
The instruction that matters most
The risk with an AI summary is not a clumsy sentence. It is a confident one the document never supported — a hedge dropped, a correlation upgraded to a cause, a figure rounded into a different claim.
The prompt is explicit about this: copy numbers exactly including units and precision, preserve qualifiers word for word, and say nothing about anything the document does not state. That reduces the risk substantially. It does not eliminate it, which is why the tool tells you to check the figures rather than implying the output is authoritative.
Why it needs an account
Reading a full document through a language model costs real compute on every run. A free Google account covers it, with no card and no trial clock — the account exists so the endpoint is not an open door.
Your document is processed to produce your result. It is not stored as a project and it is not used to train anything.
When a summary is not what you needed
Summaries solve a reading problem. They do not solve a distribution problem. If you are summarising your own document because the full version is not getting read, a shorter document will not fix that — it will be the same thing, ignored faster.
The version people finish is the narrated one: the same argument, the same figures, read aloud over visuals, watchable on a phone. That is what PDF2Video does with the document you just summarised, and the summary is a reasonable script outline for it.
Frequently Asked Questions
Is this AI PDF summarizer free?
Yes, with a free Google account and no card. The account is required because each summary runs a language model over your full document on our servers.
Can the AI get the summary wrong?
It can, in the specific way summaries go wrong: dropping a qualifier or firming up a hedged claim. The model is instructed to copy figures exactly and preserve hedging, but check the numbers against the source before relying on them.
What happens to my document?
It is extracted and passed to the model to produce your summary. It is not saved as a project on your account and is not used for training.
Why does it not work on my scanned PDF?
A scanned document is a picture of a page with no text layer, so there is nothing to read. Run it through OCR first, then upload the result.
What file types work?
PDF, DOCX, PPTX, Markdown, plain text, and VTT — the same set the main video pipeline accepts, because it is the same extractor.