What is GenDetect—and what does it deliberately not claim to be?
GenDetect is a free AI-content screening tool. Enabled detection services are selected automatically after upload consent. Provenance and model scores are shown separately, and uncalibrated results remain inconclusive.
Current scope
Free · Consent before upload · Explainable
Last updated
01 · Product scope
Evidence for an initial screen, not a decision made for you.
The site places a working detector, methodology, and verification guidance together so a user can see both a score and what that score can and cannot establish.
An online tool with no account requirement
No account or sign-up is required. Images and videos use enabled services after upload consent; text currently provides local clues. Results do not establish identity or support disciplinary or legal decisions on their own.
Text currently provides local language-pattern clues. Images use metadata, provenance and model checks; server video analysis inspects up to six sampled frames without audio or temporal analysis. Uncalibrated scores cannot establish content origin.
A result should lead to verification
Screening signals, file facts, and limitations identify what to review next. A stronger conclusion also needs the original file, content credentials, version history, an author explanation, publishing provenance, and contextual evidence—not a single detector result treated as a final verdict.
Publish the implemented capability and how it can fail.
The system selects enabled detection services and requires upload consent. Models are not yet calibrated on a representative dataset, so scores cannot establish origin and uncertain evidence remains inconclusive.
Explainable rules instead of a mysterious score
Text, image, and sampled-video indexes combine explicit observable features, and the interface exposes supporting signals. If video frames cannot be decoded, the flow reports metadata facts without a generation score. Language, genre, editing, compression, sample length, and device processing can all alter the available evidence.
Human writing can be repetitive or highly regular, and real photos can be heavily processed. AI content can also be rewritten, edited, or compressed to weaken signals. A high text or image index is not proof, a low index does not rule generation out, and video metadata cannot determine origin on its own.
GenDetect currently compares features inside the submitted material. It does not search the web, paper repositories, or publishing databases for matching sources. AI detection, plagiarism checking, fact-checking, and provenance verification address different questions and may need to be combined.
A capability change must first become a verifiable disclosure.
GenDetect uses production code and public pages as the reference. A change to the algorithm, data flow, supplier, or account capability requires corresponding methodology, privacy, and interface updates.
Describe only capabilities that have shipped
Product pages and guides do not present a planned deep model, frame-by-frame video analysis, content-credential verification, or generator attribution as a current feature. A page date identifies the public disclosure version; it is not independent certification or an accuracy endorsement.
Algorithm upgrades require new validation evidence
A future algorithm upgrade should document input scope, feature or model version, threshold rationale, representative test sets, false positives and false negatives, language or media differences, and uncovered cases before methodology and score explanations change.
Disclose the data flow before adding remote capability
Optional remote image modes now disclose upload, purpose, and deletion before submission. Any new supplier, account, or cloud-history feature must additionally name submitted fields, retention, training use, and user controls in the synchronized privacy notice.