As generated images flood the web, "is this real?" has become a product question — for marketplaces, dating apps, news, and anywhere user photos matter. AI-image detection gives you a confidence signal to act on, not a courtroom verdict.
Key takeaways
- Detectors return a probability, not a yes/no certainty.
- Cross-vendor scoring is more robust than trusting any single model.
- Use it as one signal in a decision, not the whole decision.
- You can run a check free, then wire the same capability into your app.
How detection works
Detectors look for the statistical fingerprints generative models leave behind — in textures, frequencies and artifacts the human eye misses. The output is a confidence score: how likely the image is AI-generated. Different detectors weight signals differently, so a cross-vendor read is sturdier than any one opinion.
What it's good for — and what it isn't
- Good for: triage at scale, flagging suspicious uploads for review, adding friction to obvious fakes.
- Not for: a single definitive verdict on one borderline image. Treat a high score as "look closer," not "guilty."
No detector is perfect. Build your flow so a false positive is recoverable — route high scores to human review rather than auto-banning.
Run a check now
The free AI Content Detector gives you a cross-vendor confidence score on any image, no signup. It runs on the same gateway as the API, so the production result matches what you test.
Wiring it into your app
When a one-off check isn't enough, the same capability is one API call on your withConflux key — alongside content moderation and the rest. One integration covers all of it; see what an AI gateway is.
Add a reality check to your upload flow. Try the detector free.