Visual AI likelihood
A structured score summarizes how strongly the visible details resemble patterns associated with AI-generated or AI-edited images.
Look for AI signals. Keep the conclusion honest.
Use our free AI image detector to estimate whether an image was generated or substantially edited with AI. The result is a likelihood assessment—not a claim of certainty.
Upload a photo, illustration, or screenshot to estimate whether generative AI was involved.
Free check · up to 10 MB · your image is not saved by UltraHumanizerWhat the report covers
The detector is designed to help with review and verification—not to turn one probability into a verdict.
A structured score summarizes how strongly the visible details resemble patterns associated with AI-generated or AI-edited images.
When AI-associated patterns are found, the result highlights the most relevant signals without overwhelming the core score.
The result keeps image likelihood separate from certainty and reminds you when source context or additional review still matters.
How to use it
Use the original file when possible. Screenshots and heavily compressed copies can remove useful signals.
Choose a JPG, PNG, or WebP file up to 10 MB. The browser checks its type and size before sending anything.
The server sends the image to the visual analysis model and returns a structured assessment rather than an unexplained number.
Compare the result with the source, provenance information, visible edits, and the context in which the image appeared.
Reading the score
Thresholds organize the report. They do not create certainty where the underlying model is uncertain.
Few known AI-generation signals were found. This does not prove the file is authentic or unedited.
Some signals are present, but compression, editing, illustration style, or an unfamiliar model may complicate the result.
Strong patterns associated with generated or substantially AI-edited imagery were detected. Confirm with other evidence.
Important limitations
AI image detection is an evolving classification problem. A result can shift as models, image transformations, and detector training data change.
Screenshots and compressionRepeated saving, social-media compression, or large areas of interface chrome can weaken visual signals.
Partial AI editingInpainting, generative fill, face replacement, and retouching may affect only part of an otherwise real photograph.
New or uncommon generatorsA detector can be less certain when a generator family was not represented well in its training data.
Stylized human artworkDigital illustration, heavy filters, CGI, and unusually smooth photography can resemble synthetic patterns.
Privacy by design
UltraHumanizer does not write uploaded images to its own storage or create a public URL. The selected file is held by the browser, transferred through our server to the configured AI analysis provider, and used to return the requested assessment.
Do not upload confidential client work, IDs, medical imagery, private photos, or unreleased creative assets until you have reviewed the applicable privacy policy and are comfortable with third-party processing.
privacy policy ↗Practical guide
Begin with the best available file. A screenshot of a social post may contain interface elements, resized text and compression that were absent from the original image. Upload a JPG, PNG or WebP of up to 10 MB, sign in and run the AI image checker. Read its explanation together with the likelihood band, then return to the source of the image.
Ask who first published the file, what the caption claims and whether an earlier version is available. Visible oddities can guide closer inspection, but retouching, illustration, lighting and compression can also create unusual details. A clean-looking image is not automatically a camera original, and a single unusual hand or reflection is not enough to establish how the whole picture was made.
A visual assessment is most useful when its scope is clear. UltraHumanizer reviews the uploaded pixels for AI-associated patterns; it does not provide an independent investigation into the publisher, the event or the identity of a person shown.
Scroll sideways to see all columns.
| Review step | What it adds |
|---|---|
| Run the visual model | An AI-likelihood assessment and concise visual context for the supplied image. |
| Locate an earlier source | Publication context that may explain cropping, editing or a misleading caption. |
| Inspect available provenance records | Additional information about the file’s history; verify it separately from this tool. |
| Compare an original and an edited copy | A way to narrow down where changes may have occurred. |
Frequently asked questions
Clear guidance on scores, accuracy, formats, privacy, and the limits of visual detection.
An AI image detector reviews visual patterns in an uploaded image and estimates whether generative AI was involved. UltraHumanizer currently uses a visual AI model to produce a structured likelihood assessment with concise context. It is not definitive proof of authorship or origin.
No. New generators, heavy compression, screenshots, cropping, filters, and partial AI edits can all affect a result. Use the score as one signal alongside provenance, source context, metadata, and human review.
Yes. Sign in for 3 image checks per UTC day on Free. Basic, Pro and Ultra include unlimited daily uses, subject to request and file limits. No payment is needed for the Free allowance, and Humanizer monthly words are separate.
The UltraHumanizer AI Image Detector accepts JPG, PNG, and WebP files up to 10 MB.
UltraHumanizer does not write uploaded images to its own storage. When detection is enabled, the image is transferred to the configured detection provider for processing. Do not upload confidential or sensitive images without reviewing the current privacy terms.
Not reliably. A visual model can recognize patterns that sometimes appear in generated images, but it should not be used to attribute an image to a specific generator without stronger provenance evidence.
No. A low score means the detector found fewer known AI-generation signals. It does not prove camera provenance, rule out manipulation, or establish who created the image.
One score is the beginning of a review