Review AI-written patterns with more clarity.
Run a browser-first detector pass, inspect the flagged sentences, and decide whether the draft is safe to keep, worth comparing, or needs a real rewrite.
Drop files here or click to browse
.txt, .pdf, .docx — multiple files supported
| File | Words | AI Score | Verdict |
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Drop file here
.txt, .pdf, .docx
Detection results and saved tasks appear here
Paste at least 30 words, analyze once, then continue the task, share the result, or save it locally in this browser.
Recent Tasks
Analyzing patterns...
Running multi-model detection
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Result explanation
Run a detection pass to see what the score means.
The result panel will explain how to interpret the score, what it means for this draft, and which next step makes the most sense.
What this means
Use the score as a review signal, then inspect the highlighted passages before you decide on the next action.
Main risk
High-stakes text should not rely on a single detector result without sentence review or a second opinion.
Trust it when
Treat this as a bounded review signal when the sentence highlights and the draft context tell the same story.
Retry or switch path when
Switch to compare, humanize, or rewrite when the highlighted lines and the draft context no longer match your confidence threshold.
Anchor the detector result to reusable interpretation assets.
These proof slots turn detector interpretation into reusable assets: a low-risk anchor, a high-risk anchor, and a misread boundary that can keep growing without changing the product language.
A low-risk draft usually has only a few highlighted lines, visible sentence variation, and enough human texture that manual cleanup is often enough.
Use this anchor when the score is low and the highlighted lines still look like isolated watchpoints, not a clustered detector pattern.
Continuation stays manual first unless compare or cleanup is justified by the same highlighted lines.
A high-risk draft usually shows repeated uniform phrasing across several highlighted sentences, which is why compare becomes the first credible switch.
Use this anchor when several flagged lines cluster together and the detector result matches what manual review already suspects.
Continuation starts with compare, then moves to humanize or rewrite only if the second opinion and the highlighted pattern still agree.
The detector is a bounded review signal, not proof of authorship or intent. Templated human writing and lightly edited AI drafts can both create mixed readings.
Use this slot to separate genuine detector risk from over-reading a score without context.
The boundary asset decides when to stay in manual review and when a second detector or rewrite path is actually warranted.
Use detector-specific benchmarks before you act on the score.
Phase 27 turns the proof layer into route-specific detector behavior: low-risk review, high-risk compare, and misread-boundary guardrails.
Benchmark against drafts with isolated highlights, normal sentence variation, and enough context to stay in manual review before changing the text.
Benchmark against drafts where flagged lines cluster across the same tone or structure, making compare the first credible second-opinion path.
Benchmark against templated human writing and lightly edited AI drafts so the detector stays a bounded signal, not an authorship claim.
Turn each detector benchmark into trust, action, and saved-job evidence.
Shared benchmark language stays consistent across the flagship suite: benchmark pattern -> trust signal -> action path -> saved posture.
Log whether the result matched low-risk review, high-risk compare, or misread-boundary guardrails before recommending a next step.
Map the benchmark to manual review, compare, humanize, or rewrite so continuation is earned by the current detector pattern.
Keep the local saved task tied to the benchmark name and short share summary, not just the raw score.
Shareable summary
Recommendation path
Share note
Decision guide
Run a detection pass first so the next step is based on the actual result.
Compare with GPTZero
OptionalUse compare when you need a second detector perspective before changing the draft.
Humanize flagged text
OptionalUse humanizer only after you know which lines are creating detector risk.
Rewrite risky sections
OptionalUse rewriter when the detector issue is broad enough that a few sentence edits will not be the cleanest fix.
Primary path and alternate path will update after the result so you know when to keep the current draft, when to compare, and when to switch into rewrite or humanize.
Continue a recent result or pin it as a saved task.
Detector task history stays local to this browser and only keeps bounded task metadata.
Only single-text detector tasks are stored in `localStorage` on this device. Nothing here syncs to an account, team, workspace, API, or server database.
Local detector tasks auto-expire after 30 days. Delete any single card from Recent or Saved, or use `Clear local tasks` to wipe everything now. Batch runs, downloads, and copied/shared summaries are not kept as long-term history.
Resume detector, PDF, and image work from one local entry point.
This cross-suite job home keeps detector, PDF, and image jobs in one local-first place so you can return from saved work or continue the latest task hierarchy.
Everything here stays in `localStorage` on this browser only. Nothing syncs to an account, server, team, workspace, or API.
Recent jobs surface what you touched last. Saved jobs pin the items you expect to revisit later. Each card keeps the primary path first and the alternate path second.
Shared summaries travel outside the app. Saved jobs stay here as your local return point with the proof memory that explained why the next step was trusted or switched. Clear or delete any item when you no longer want it kept for up to 30 days.
This stays free and local-first today. If real before/after evidence, bookmark, email, sync, account-level memory, export packs, or shared handoff layers come later, they should extend saved proof context without blocking the free local job now.
Keep the free detector path complete, and keep the upgrade boundary honest.
The free path should already solve the real detector job: run locally, inspect sentence-level proof, save or share the summary, then continue into compare, humanize, or rewrite.
Local detection, sentence review, next-step guidance, and local-first saved jobs stay usable without forcing an upgrade decision first.
If premium depth grows later, it should extend real tasks like denser review packs or stronger proof summaries, not block the current detector workflow.
Keep detection history across devices
Saved tasks on this page stay local. Create an account if you want synced history and exported reports later.
Create Free AccountNeed detection at scale?
Our API lets you check thousands of documents programmatically.
View API plans →| # | Sentence | AI Score | Verdict |
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Analysis Details
Use the detector as a review workflow, not a verdict button.
Paste a real draft
Use enough text for the detector to see sentence context, not just isolated fragments that can overstate or hide a pattern.
Review the hotspots
Look at the score together with sentence-level highlights, explanation cards, and benchmark guidance before you decide what the result means.
Choose the next path
Keep the draft, compare it against GPTZero, humanize flagged lines, or rewrite broader sections only when the evidence points that way.
What the detector actually analyzes.
Sentence pattern review
The detector checks variation in sentence structure, vocabulary, and rhythm to spot language that feels too uniform or mechanically predictable.
In-browser model score
The RoBERTa detector runs on the page and estimates whether the wording resembles common AI-generated text patterns.
Combined interpretation
The final read blends the model result with pattern evidence so a single signal does not decide the whole judgment on its own.
Built for review contexts where a single score is not enough.
Screen student submissions
Run a first-pass integrity check, then inspect the flagged lines before you decide whether a draft needs a conversation, not just a score screenshot.
Audit your own draft
If you used AI for brainstorming or outlining, the detector can help you see whether the finished submission still carries patterns you want to revise first.
Review client or contributor copy
Check whether a draft needs a second detector opinion, light human cleanup, or a broader rewrite before it enters an editorial workflow.
Stress-test formal writing
Academic and report-style prose can trigger false positives, so sentence-level review is useful when you need to distinguish template-like structure from actual detector risk.
Start free, keep the first-pass review intact.
Browser-first checks, sentence review, local saves
Higher usage, shared writing suite access, faster workflows
Higher-volume usage, team-ready workflows, API access
Dig deeper into AI detection.
Best-of lists
Terms explained
What people ask before they trust a detector result.
How accurate is the AI detector?
Can I start using the detector right away?
What file formats can I upload?
Can I humanize the detected text?
Why does the first analysis take longer?
Which AI tools does it detect — ChatGPT, Claude, Gemini?
Why might my human-written text score as AI?
Is my text sent to any server when I analyze it?
How does access work compared with other writing tools?
Do I need to create an account?
Can I pay with cryptocurrency?
Is it safe for academic use?
Does it work on mobile?
Is there a Chrome extension?
How does this compare to GPTZero?
Coda One's AI Content Detector is built for browser-first screening with sentence-level context. Use it to inspect flagged passages, compare the result when needed, and only move into humanizing or rewriting when the evidence stays consistent across the draft.
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