How accurate is the detection compared to other tools?

Most single-model detectors have known blind spots and systematic biases. DeepSight uses a multi-signal cascade that cross-checks forensic signals, achieving meaningfully higher accuracy across a wider range of generators. We report confidence scores rather than binary yes/no answers.

Can I use DeepSight for images from social media?

Yes. You can paste a URL directly from social media platforms. DeepSight will fetch and analyze the image. Note that heavy compression from social platforms may reduce forensic signal strength, which is reflected in the confidence score.

Is there an API for integrating into our newsroom workflow?

Yes. Our REST API supports programmatic analysis with JSON responses, making it straightforward to integrate into CMS workflows, Slack bots, or editorial verification pipelines. Enterprise plans include higher rate limits and webhook support.

deepsight

For Journalists

Never publish a fake image again

AI-generated images are flooding newsrooms faster than editors can verify them. DeepSight gives journalists a forensic-grade verification tool that works at the speed of breaking news — so you can trust what you publish.

Verify an image now

900%

Increase in AI-generated images since 2022

<3s

Average analysis time per image

30+

Generator models identified

The Challenge

What journalists are up against

Fake images in submissions

Citizen journalists, tipsters, and wire sources increasingly submit AI-generated imagery. Without detection tools, a single synthetic photo can undermine an entire story and erode reader trust built over decades.

Source verification under pressure

Deadline pressure means verification shortcuts. When a breaking story demands immediate visuals, there is no time for reverse image searches, EXIF manual inspection, or waiting for a forensics team to respond.

Coin-toss accuracy from other tools

Independent benchmarks show most AI image detectors perform no better than a coin toss, with a systematic bias toward labeling AI images as real. Journalists need a tool they can actually rely on.

Reputational risk at scale

A single published fake can go viral, spawn corrections, and become the story itself. The reputational damage to a news organization from publishing AI imagery is disproportionate to the cost of prevention.

The Solution

How DeepSight helps

Multi-signal forensic analysis

DeepSight does not rely on a single model. Our cascade examines metadata provenance, statistical forensics, visual analysis, and specialized APIs — cross-checking signals so a weakness in one is compensated by the others.

Results in seconds, not hours

Upload an image and get a confidence-scored verdict in under three seconds. The analysis runs through multiple forensic layers automatically, returning a detailed report you can cite in your verification process.

Generator identification

DeepSight does not just flag synthetic images — it identifies the likely source generator (Midjourney, DALL-E, Stable Diffusion, Flux, and 30+ others), giving you actionable intelligence for your reporting.

Audit trail for editorial standards

Every analysis produces a forensic report with confidence scores, signal breakdowns, and methodology notes. This provides the documentation editorial teams need for their verification records.

Your Workflow

How it works

Receive a photo from a source, wire service, or social media

Upload the image to DeepSight or paste the URL

Review the forensic report: verdict, confidence score, and generator identification

Cite the verification in your editorial notes and publish with confidence

Common Questions

Frequently asked

Yes. DeepSight returns results in under three seconds. Upload the image or paste a URL, and the forensic analysis begins immediately. There is no queue, no wait time, and no manual review step required.

See it in action

Upload an image and watch the multi-signal cascade work — metadata, forensics, and semantic analysis in real time.

Verify an image now