Question 1

How does AI image detection work?

Accepted Answer

Reality AI runs multiple detection models simultaneously: AI generation detection identifies patterns left by generative models, deepfake detection analyzes facial regions for manipulation artifacts, metadata forensics checks EXIF data and compression signatures, and pixel-level analysis examines noise patterns and frequency domain anomalies. According to NIST research on media forensics (2024), ensemble detection methods outperform single-model approaches by reducing false positive rates by up to 40%.

Question 2

Which AI generators can Reality AI detect?

Accepted Answer

Reality AI detects images from DALL-E, Midjourney (v5-v6.1), Stable Diffusion (1.5-3.0), Flux (Pro/Schnell/Dev), Adobe Firefly (2-3), Leonardo.ai, Runway Gen-2/Gen-3, Ideogram (1-2), Playground, Bing Image Creator, Google Imagen (2-3), and Canva AI, among 100+ other generators. Detection coverage is updated as new models release, with an average accuracy of 94% across tested generators per internal benchmarks.

Question 3

How accurate is AI image detection?

Accepted Answer

Reality AI achieves 94%+ accuracy on common AI-generated images and 89%+ on advanced deepfakes, per internal benchmarks. The platform provides a confidence score with every analysis. Using multiple detection methods in parallel, the ensemble approach catches manipulations that any single model would miss. For high-stakes use cases, a certified expert review is available.

Question 4

Is my uploaded image stored or shared?

Accepted Answer

Images are processed in memory and automatically deleted within 24 hours. We do not use your images for model training, share them with third parties, or retain any personally identifiable information. Reality AI is SOC 2 Type II certified and GDPR compliant, with AES-256 encryption at rest and TLS 1.3 in transit. EU and US data residency options are available for enterprise plans.

Question 5

Can Reality AI detect manipulated images?

Accepted Answer

Yes. Beyond AI generation detection, Reality AI identifies image manipulation including face swaps, splicing, cloning, retouching, and metadata tampering through pixel-level inconsistency analysis. The platform uses 6+ forensic methods including error level analysis, JPEG ghost detection, and noise pattern comparison.

Question 6

Do you provide AI expert witness testimony for court?

Accepted Answer

Yes. Reality AI provides certified AI expert witness services for litigation. Our deepfake forensic experts testify in depositions and at trial, providing Daubert-compliant expert reports on AI-generated images, deepfakes, and manipulated digital evidence. We also provide sworn affidavits and chain-of-custody audit trails. Expert witness engagements have supported cases in federal and state courts.

Question 7

What is included in a deepfake forensic report?

Accepted Answer

Our AI forensic report for court includes GAN detection analysis, metadata forensics, pixel-level manipulation detection, frequency domain analysis, content credential (C2PA) verification, and a detailed methodology section. Reports meet federal evidence standards (Daubert v. Merrell Dow) and include chain-of-custody documentation. Expert witness testimony to support findings is available.

Question 8

How can I use Reality AI for EU AI Act compliance?

Accepted Answer

Article 50 of the EU AI Act requires mandatory labeling of AI-generated content, with enforcement beginning August 2, 2026. Reality AI can scan your content library to identify unlabeled AI-generated images before the deadline. The platform generates audit reports suitable for regulatory submissions under the EU AI Act's transparency requirements.

Building the trust layer for visual content.

Make visual authenticity verifiable at scale

AI image fraud is growing exponentially