Free · Fast · Privacy-first

Check AI Writing Before Submitting

Whether you are a student preparing a term paper, a freelance writer delivering to a client, a job seeker submitting a written application response, or a grant writer finalizing a proposal, submitting work that reads as AI generated can carry real consequences.

⚡

Pre-submission AI pattern check

🔒

Identifies specific flagged sentences

✨

Free, private, no account needed

⚡

Works for all writing types

Cost: Free forever
Sign-up: Not required
Processing: In your browser
Privacy: Files stay local

FreeNo signupWhite-label

Add this AI Content Detector to your website

Drop the AI Content Detector into any page — blog post, product docs, intranet, school portal — with a single line of HTML. Your visitors get the full tool, processed entirely in their browser. No backend, no uploads, no signup.

Files stay 100% in the visitor's browser
Responsive — adapts to any container width
Free forever, no API key needed

Embed code

<iframe
  src="https://www.fixtools.io/aitools/ai-content-detector?embed=1"
  width="100%"
  height="780"
  frameborder="0"
  style="border:0;border-radius:16px;max-width:900px;"
  title="AI Content Detector by FixTools"
  loading="lazy"
  allow="clipboard-write"
></iframe>

<iframe
  src="https://www.fixtools.io/aitools/ai-content-detector?embed=1"
  width="100%"
  height="780"
  frameborder="0"
  style="border:0;border-radius:16px;max-width:900px;"
  title="AI Content Detector by FixTools"
  loading="lazy"
  allow="clipboard-write"
></iframe>

Attribution-friendly: a small "Powered by FixTools" link appears in the embed footer.

Pre-Submission AI Screening: Catching Problems Before They Catch You

The number of contexts where AI screening now happens before written work reaches a human reviewer has expanded dramatically in the past two years. Universities run student submissions through Turnitin AI detection automatically. Publishers require human written content from contributors and screen incoming articles before accepting them. Content agencies screen freelancer deliverables to catch chatbot output that violates contracts. Grant committees flag AI generated application narratives. Job platforms screen written application responses on behalf of employers. Trust and safety teams at major platforms run user generated content through detection at scale. If your writing workflow involves any AI assistance at any stage, the prudent final step is to run a pre submission check yourself so you find any flag worthy passages before someone else does.

AI writing tools leave fingerprints in your final draft even after substantial revision, in ways that surprise most writers when they first encounter them. The patterns are embedded not just in obvious phrases but in word choice frequencies, sentence rhythm, transitional vocabulary, and structural habits that writers unconsciously preserve when they edit rather than fully rewrite. A draft generated by a chatbot and then edited paragraph by paragraph by a human typically still scores 40 to 60 percent on detection tools, because the underlying rhythm of the original generation persists through surface changes. Genuine rewriting, where you read each paragraph and then write your own version from scratch without looking at the original, is what actually drops detection scores into the safe range.

A pre submission score below 20 percent is a strong signal that your writing reads as your own. A score between 20 and 50 percent warrants a targeted review of flagged sentences and probably some rewriting before submission. A score above 50 percent indicates meaningful AI residue that needs more substantial revision regardless of your time pressure. For academic contexts where institutional policies are strict, aim for the lowest score you can achieve through genuine rewriting in your own voice. For professional and editorial contexts, ask what threshold your recipient uses if you can, and aim well below it to give yourself margin against scoring variation between detection tools.

The privacy of running checks on your own draft matters as much as the result. FixTools processes everything in your browser, which means the unpublished work you paste never leaves your device and never gets stored anywhere. You can check a confidential thesis chapter, an unpublished manuscript, a sensitive client deliverable, or a personal statement for a graduate application without any risk that the content will be indexed, retained, or used for training. The privacy guarantee makes pre submission checking a safe routine step rather than a calculated risk, which means you can build it into your writing workflow as a normal final pass alongside spell check and citation review.

Scribbr Guide to AI Detectors and Academic Integrity Journal Publishing and AI Writing Policies (Nature)

How to use this tool

💡

Paste your final draft. The tool shows which sentences pattern-match to AI writing so you can revise before submitting.

How It Works

Step-by-step guide to check ai writing before submitting:

1
Finalize your draft
Complete all the substantive edits and structural revisions on your document before running the AI check. Checking earlier draft versions wastes effort on content you have already decided to change, while checking the actual submission version gives you a true preview of what reviewers will see when they evaluate your work.
2
Paste into the detector
Copy the full text of your finalized draft and paste it into the FixTools AI Content Detector input field. Plain text gives the cleanest reading, so route formatted documents through a plain text intermediate first if you can. Aim to capture the body of the work without metadata such as headers, footers, or page numbers that did not come from your writing.
3
Identify AI-sounding sections
Note both the overall score and the specific sentences highlighted as AI probable. Concentrated highlighting in a few paragraphs tells a different story from scattered highlights across the whole document, and the sentence level information is usually more useful than the aggregate number for deciding what to revise.
4
Revise and recheck
Rewrite each flagged passage in your own voice, adding specific detail, varying sentence structure, and replacing generic phrasing with content drawn from your own knowledge and experience. After revising, run the detector again on the new version to confirm the score has dropped into your target range before submitting your final work.

Real-world examples

Common situations where this approach makes a real difference:

Thesis draft review

A second year graduate student writing a literature review chapter used a chatbot to help structure the historiography section, then rewrote the prose in her own voice over two weeks. Before her advisor meeting she pastes the full chapter into the detector and finds the historiography section still scores 64 percent while the rest is below 20 percent. She spends an evening doing a real rewrite of that section, drops the score to 18 percent, and brings clean work to the meeting.

Freelance writer quality check

A content writer who uses chatbots to draft initial outlines and then composes the actual articles himself maintains a strict pre delivery check. Every article goes through the detector before it leaves his inbox. His contract specifies human written work and he treats anything above 25 percent as triggering a rewrite pass. The discipline has earned him repeat business from clients who specifically value the guarantee of original prose.

Grant proposal screening

A nonprofit grant writer preparing a major foundation application learns that the foundation has begun screening narratives for AI content as part of their review process. Before submitting she pastes the entire narrative through the detector, identifies two paragraphs that score above 60 percent, rewrites them with specific program data and beneficiary quotes from her case files, and submits a final version scoring 14 percent overall.

When to use this guide

Use this immediately before submitting any piece of writing, especially if you used AI tools during any stage of drafting, outlining, or editing, to confirm the final text reads as authentically human.

Pro tips

Get better results with these expert suggestions:

Target the flagged sentences specifically, not the whole document

When your overall score comes back higher than you wanted, resist the temptation to rewrite the entire document from scratch. Focus your revision time only on the specifically highlighted sentences, since those are the ones driving the score. Targeted rewriting of flagged passages is dramatically more efficient than a full redraft and typically produces better results, because you can put real attention into making those specific passages reflect your voice rather than spreading effort thinly across content that was already fine.

Add a specific data point or anecdote to each flagged paragraph

The single most effective technique for reducing detection scores in academic or professional writing is to insert a concrete specific detail into each flagged paragraph. A real statistic with a current date, a named source with a verifiable quote, a personal example from your experience, an original observation from your research, or a piece of program data from your own work all shift the statistical profile of the writing significantly. These additions are exactly the elements a chatbot could not have produced, which is precisely why they break the detection signature.

Check the document in its final format

If your submission will go through as a Word document, PDF, or web form, finalize the formatting before running your detection check and then copy the plain text from the finalized version into the detector. Some formatting and export operations subtly change how text reads, particularly around quotation marks, dashes, and special characters. Checking the version that is as close as possible to what you will actually submit gives you the most accurate preview of what reviewers and detection systems will see on their end.

Run the check the night before, not minutes before

Build a buffer of at least several hours, and ideally overnight, between your pre submission check and your actual submission deadline. Rushed rewrites done in the last fifteen minutes before a deadline usually just rephrase the flagged AI text rather than genuinely replacing it with your own voice, because there is no time to think carefully about what you actually want to say. An overnight gap lets you revise from a rested perspective the next morning, which produces meaningfully better writing and substantially lower detection scores.

Always check after AI-assisted drafts

Even if you wrote the majority yourself, any AI-assisted sections can drag up the overall score. Run a final check to identify which sentences to rewrite.

Read flagged sentences aloud

AI-generated text often sounds smooth but impersonal. Reading flagged sections aloud helps you identify where to inject personal voice, specific examples, or opinion.

Set a target score before submitting

Aim for a score below 20-30% AI probability before submitting to institutions or publications with strict AI policies.

FAQ

Frequently asked questions

Yes, with FixTools specifically. The entire detection process runs in your browser, which means the text you paste never travels to a FixTools server, never gets stored anywhere on our infrastructure, and never becomes training data for any model. This makes it safe to check sensitive content including unpublished research, proprietary client work, confidential business writing, personal statements for graduate applications, and other material you would not want indexed or shared. Closing the browser tab clears the in memory copy completely. Other detection tools may have different privacy practices, so always check before pasting sensitive content into unfamiliar services.

Use of detection has become routine across academia, journalism, content marketing, and many regulated industries, and the practice is still expanding rapidly. Major academic publishers, large news organizations, and most content platforms have introduced AI content policies in recent years, with enforcement typically including some form of automated detection. Smaller publications, individual editors, and informal contexts vary more, but the safe assumption for any consequential submission is that some form of screening is likely. Running your own check first is the easy way to make sure that screening surfaces no surprises.

Some formal writing styles can occasionally produce elevated scores on authentic original work because they share structural features with chatbot output: longer sentences, more conservative word choices, and a more uniform register. Academic writing in technical fields, formal corporate communications, careful prose by non native English speakers, and template driven content are the most common sources of higher than expected scores. If you know your writing is genuinely your own and the score concerns you, the most effective response is to add more specific examples, vary sentence lengths deliberately, and include details that a chatbot could not have generated, which both improves the writing and lowers the score.

For routine submissions, one check on the final draft is usually sufficient. For higher stakes work, a more thorough workflow runs an initial check to identify the overall score, makes targeted revisions to flagged passages, runs a second check to confirm improvement, and runs a third final check after any last edits to confirm the score has not drifted upward. The whole multi pass workflow takes only a few minutes once you have done it a few times, and the additional confidence is worth the modest time investment for academic dissertations, grant applications, professional editorial submissions, and similar consequential work.

For academic submissions, a score below 20 percent is generally safe at most institutions. For professional editorial contexts and content platforms, below 25 to 30 percent is typically acceptable, though specific publisher policies vary. For situations where you do not know the specific threshold, target the lowest score you can achieve through genuine revision rather than aiming for a particular number. The principle behind every threshold is the same: detection systems are looking for prose that does not pattern match to chatbot output, and writing that genuinely sounds like a thinking human author satisfies that requirement regardless of the specific cutoff a given system uses.

Yes, and this is one of the more underrated uses of the tool. Running your own writing through the detector and reviewing which sentences get flagged is an effective way to identify where your phrasing has become generic, template like, or impersonal in ways that read as machine like even though you wrote them yourself. The flagged sentences are your signal to inject more specific detail, vary your sentence structure, develop your distinctive voice, and replace empty connective phrases with content that actually advances your argument. Writers who do this regularly report meaningful improvements in their natural style over several months of feedback.

The detector works best on natural language prose such as essays, articles, reports, letters, personal statements, and other flowing written content. It is less reliable on highly structured formats such as resumes with bullet points dominating the content, legal contracts with templated clause structures, or technical specifications dense with jargon and numbered requirements. For code, mathematical notation, or pure tabular data, the tool is not a meaningful check. For the broad middle of normal written communication, including most academic and professional writing, it produces reliable and useful results.

Translated text occupies an interesting middle ground. Translation often produces prose that is more uniform in rhythm than original writing in the target language, particularly when the translator is working carefully and conservatively. As a result, translated content sometimes scores higher than original prose of the same quality. This is a known limitation rather than a flaw, and it means you should weight context carefully when evaluating translated work. For your own translated writing, the same revision principles apply: adding specific detail and varying sentence structure improves both the writing and the score.

Different detection tools use different classifier models with different calibration, which means the same input can produce scores that differ by 10 to 20 percentage points across tools. If you know which detector your recipient uses, aim for a score on FixTools that gives you margin against that variation, typically 10 percentage points below their stated threshold. If you do not know which detector they use, target the lowest score you can reasonably achieve through genuine revision, which gives you the best chance of clearing whatever specific system you eventually face on the receiving end.

Yes. You can paste a single paragraph or even a few sentences into the detector and get a score, though accuracy is somewhat reduced on shorter samples because the statistical analysis has less material to work with. For a quick spot check on a specific paragraph you suspect, paste just that paragraph. For a more reliable read, paste at least 200 words including the surrounding context, which gives the classifier enough text to produce a stable score and lets you see whether the suspected passage stands out against the surrounding material.