SPRIND Deepfake Detection Challenge Winner

Frame:Detect

Ultra-high accuracy AI image detection engine. Multi-model ensemble that fuses several specialized models and dozens of forensic signals into one meta-model, validated as the best-performing system in the SPRIND Challenge.

Frame:Detect · Analysis Live
upload_img_7291.jpg 3.1 MB
Lightning
89%
Diffusion Patterns
76%
Metadata Analysis
94%
Noise Fingerprint
82%
Likely AI-Generated Risk: 0.87

Core capabilities

Multi-layer forensic image analysis: several models, dozens of signals, one meta-model.

Multi-model ensemble

We fuse several specialized detection models and dozens of forensic signals into one meta-model, delivering a single calibrated risk score with ultra-high accuracy.

Sub-second processing

Typical analysis completes in under 2 seconds. Designed for real-time pipelines where speed matters: content moderation, upload screening, claim verification.

Full-spectrum format support

JPEG, PNG, WebP, TIFF, and BMP. Up to 10 MB per file. No preprocessing required. Send the original file as-is.

Signal Breakdown
Lightning
92%
Diffusion Patterns
78%
Metadata Analysis
96%
Noise Fingerprint
85%
Meta-model fusion Risk: 0.91

Multi-layer forensic analysis

Every image passes through several specialized detection models and dozens of forensic signals. A meta-model fuses the outputs into a single, calibrated risk score.

Frame Detection Models
Multiple Vision Transformer models trained across all major generator architectures.
Technical Analysis Signals
Spectral, spatial, statistical, and compression forensics: dozens of low-level signals.
Semantic & Visual Interpretations
Object coherence, lighting consistency, and anatomical plausibility.
Metadata & C2PA Provenance
EXIF integrity, encoding artifacts, software fingerprints, and C2PA Content Credentials.
ItsReal.media is a member of the C2PA Coalition. actively contributing to the standard for content provenance and authenticity.
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Accuracy on real images

SPRIND Challenge evaluation, November 2024

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CMB Bench accuracy

Real-world conditions: compressed, resized, re-uploaded images

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Internal validation accuracy

Across full test suite under controlled conditions

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SPRIND Challenge ranking

Winner, Bundesagentur für Sprunginnovation

Use cases

Where Frame:Detect fits into your workflow.

Media newsrooms

Screen wire photos and user-generated content before publication. Protect editorial integrity with automated AI detection at the point of ingestion.

E-commerce platforms

Detect AI-generated product photos and synthetic lifestyle images. Ensure listing authenticity across your marketplace.

Insurance claims

Verify damage photos submitted with claims. Flag AI-inpainted or entirely synthetic evidence before it reaches adjusters.

Social media

Add AI detection to your content moderation pipeline. Automatically flag synthetic uploads before they spread across the platform.

Start detecting

Talk to the team about integrating Frame:Detect into your pipeline. We run the full detection stack against your sample images.