AI Text Analyzer

What goes wrong when a document is never properly analysed? It gets approved. Somebody reads it once, nothing obvious jumps out, and the weak argument in the third section survives into a decision. AI Text Analyzer exists to give a document the second reading that nobody has time for.

What is AI Text Analyzer?

AI Text Analyzer is a free browser tool that reads a piece of text critically. Its prompt box asks for what you want analysed, and the input can be anything argumentative: a proposal, a report, a policy draft, a set of customer responses, a piece of writing you are about to send.

Why Use AI Text Analyzer?

Because you cannot analyse your own writing. You know what you meant, which means you read the intention rather than the words, and the gap between the two is invisible to you and obvious to a reader who arrives cold.

The second reason is timing. Analysis is worth most before a document is sent, and that is exactly the moment when nobody wants to spend an hour on it. Making it a five minute step means it actually happens at the point where the findings can still be acted on.

Who Should Use It?

Anyone about to send something that will be scrutinised. Bid writers checking an answer before submission. Managers reviewing a proposal from their team. Consultants pressure testing a report. Students checking whether their argument holds. Editors deciding whether a piece is finished.

How Does AI Text Analyzer Work?

The tool sits on one page. Its prompt box carries the placeholder Paste or describe what you want analyzed for the text analyzer. Below it is the model row, and whichever model is selected there handles the run. The advanced options accordion and the generate button follow.

The analysis arrives in a card with a running word count in the footer, which is a small but genuine help when the analysis itself has to fit into a review document. Copy, listen, reuse, download and open in full view sit on the card, a DOC, TXT and HTML export row runs alongside, and the session history panel keeps each run listed below.

Step-by-Step Guide

1. Decide what you actually want to know before choosing any setting.
2. Paste the text, stripped of anything personal.
3. Pick a model.
4. Set the analysis focus to your question rather than to Overview by reflex.
5. Set rigor to match how much scrutiny the document will face.
6. Generate, then rerun on a second focus if the first read raised something.

A short check before you rely on an analysis:

• ✅ You pasted the whole argument, not one section of it
• ✅ The focus matches the question you brought
• ✅ Rigor matches the scrutiny the document will actually face
• ✅ Personal identifiers were removed first
• ✅ You know which findings are about support and which are about accuracy

Advanced Options Guide

The accordion sits closed beneath the model row, and opening it is the second thing most people do. It matters from the second run, when you know what you want to interrogate.

Example Inputs

The most useful input is a whole argument rather than an extract. Here is a realistic paste into the AI Text Analyzer:

Analyse as a sceptical procurement officer looking for
unanswered requirements. High rigor. Flag anything asserted
without support.

"Our approach reduces onboarding time significantly. We have
worked with organisations of a similar size and have always
delivered on schedule. Our team is highly experienced and our
process is proven. Implementation typically takes six to eight
weeks, although this can vary depending on circumstances. We
will assign a dedicated project lead throughout."

Six sentences, five of which assert something and none of which supports anything. That is a very common shape for a submission paragraph, and it is exactly what a rigorous analysis is for.

Example Outputs

With focus on Gaps, rigor high and the procurement reader named, the analysis returned this:

UNSUPPORTED CLAIMS

"reduces onboarding time significantly"
  No baseline, no comparison, no figure. Unassessable.

"organisations of a similar size"
  Similar in what respect? Sector, headcount, complexity?

"always delivered on schedule"
  Absolute claim with no evidence. A single counterexample
  from a reference call destroys it. Weaken or support it.

"highly experienced" / "process is proven"
  Both are assertions about quality with nothing behind them.

CONDITIONAL LANGUAGE THAT REMOVES THE COMMITMENT

"typically takes six to eight weeks, although this can vary"
  This states no obligation. A procurement reader will treat
  it as no timescale offered at all.

WHAT IS ACTUALLY COMMITTED
One thing: a dedicated project lead.

That closing count is the most uncomfortable line in the report and the most useful. A paragraph of confident writing that commits to exactly one thing is worth knowing about before somebody else points it out.

Once the edits are made, a compression pass with the AI Text Summarizer is a quick way to check that the argument still reads clearly when reduced to its bones.

AIToolsay is the starting point for the rest of the workflow, and an analysis is only useful if something follows it. The findings become edits, the edits need rewriting, the rewritten version usually needs checking again, and eventually the whole thing needs shortening to fit. Each has a tool of its own, and the layout is constant from one to the next: the same prompt box, the same model row, the same options accordion, the same export controls, the same session history panel. Every one of them free, every one open, and every one compatible with the last.

Frequently Asked Questions

Run it on the paragraph you are proudest of. That is where the unsupported claims usually live, because confident writing and evidenced writing feel identical from the inside.

Thank you for reading. Our Telegram community receives announcements first, larger releases go out by push notification, and the newsletter provides the monthly overview. The rest of the catalogue is at AIToolsay.

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