AI Text Summarizer

It reads your text, works out which sentences carry the most meaning, and returns those in their original order. The result is a shorter version that still reads as connected prose rather than a list of disconnected fragments.

Ranking uses TextRank, the same family of algorithm behind Google's original PageRank. Every sentence is compared with every other sentence, and those that share the most meaningful vocabulary with the rest of the document score highest — the logic being that a sentence connected to many others is probably central to the argument. Opening sentences get a modest boost, because articles tend to state their point early.

You control the length with three settings — short keeps roughly 15% of the sentences, medium 30%, long 50% — and you can switch between a flowing paragraph and a bulleted list of key points.

Most reading is triage. You have twelve open tabs, a long report and twenty minutes, and the real question is which of them deserves your full attention. A summary answers that in seconds.

The word counts and reading times sit next to each other so you can see the trade directly: a 2,400-word article at twelve minutes becomes 700 words at three and a half. That is the number that matters when you are deciding what to read properly.

It is equally useful on your own writing. Running a draft through it shows which sentences the algorithm considers load-bearing — and if the ones you thought were central do not appear, that usually means they are not as clearly written as you assumed.

The key terms panel doubles as a quick check on subject matter, which is handy when you are scanning research or checking whether an article actually covers what its headline promised.

Every sentence in the summary is taken verbatim from your text. Nothing is reworded and nothing is generated, which means the tool cannot hallucinate a fact, invent a statistic or misattribute a quote — the failure mode that makes people wary of AI summaries in the first place.

The trade-off is that the output is only as smooth as the sentences it picked. A summary of tightly written prose reads beautifully; a summary of rambling text will contain rambling sentences, because those are the sentences that were there.

This suits anything where accuracy matters more than polish: research papers, legal documents, meeting notes, news articles, technical documentation. If you need the summary rewritten in a different voice, that is a job for a language model, and you should check its output against the original.

Give it enough to work with. Below about five sentences there is nothing meaningful to rank, so the tool returns your text more or less intact. Several paragraphs is the sweet spot, and it handles articles of several thousand words comfortably.

Strip navigation and boilerplate before pasting. Cookie notices, menu items and footer text pasted from a web page are treated as sentences and can pull the ranking off course.

Start on medium and adjust. If the summary drops something you consider essential, move to long rather than assuming the tool missed it — often the sentence is ranked just below the cut.

Use key points for meeting notes and reference material, and paragraph for anything you plan to read or share as prose.

No. The entire algorithm runs in JavaScript on your own device. There is no API call, no server, no model and no account — nothing you paste is uploaded, stored or logged.

That is a genuine difference from most summarising tools, which post your text to their backend. If you are summarising anything confidential — client documents, unpublished work, internal reports — that distinction matters.

It also means the tool works offline once the page has loaded, and returns results instantly instead of queueing behind an API.