Can scammers bypass detection with post-processing?

Our multi-signal cascade is designed to be resilient against adversarial post-processing including re-compression, color grading, cropping, and noise addition. An attacker would need to defeat multiple independent forensic signals simultaneously, which is significantly harder than fooling a single-model detector.

How do I integrate this into our existing upload flow?

DeepSight provides a REST API that returns results in under three seconds. Most teams add a middleware step between photo upload and profile activation. We provide SDKs and integration guides for common platforms and frameworks.

What about AI-enhanced real photos?

DeepSight detects both fully AI-generated images and significantly AI-modified ones. The confidence score reflects the degree of synthetic content detected. Minor AI enhancements (like background blur) typically score below the threshold, while AI-generated portraits from scratch score high.

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For Dating Apps

Keep real people on your platform

AI-generated profile photos power a new generation of catfishing, romance scams, and bot networks. DeepSight helps dating platforms detect synthetic profile images at upload, protecting users and preserving the trust that makes your platform valuable.

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19%

Of UK singles have been duped by AI-generated photos

<3s

Real-time analysis during photo upload

~$0.006

Cost per profile photo analyzed

The Challenge

What dating apps are up against

Catfishing at scale

AI generators produce photorealistic portraits in seconds, enabling catfishers to create convincing fake profiles with zero effort. Each fake profile degrades the experience for genuine users and increases churn.

User trust and safety

Users who encounter fake profiles — or worse, fall victim to romance scams — leave the platform and warn others. Trust is the foundation of dating platforms, and synthetic profiles erode it systematically.

Platform integrity and metrics

Fake profiles inflate user counts while degrading engagement quality. They distort matching algorithms, waste genuine users' time, and create misleading growth metrics that mask underlying problems.

Deepfake-enhanced scams

Sophisticated scammers now use AI to generate not just profile photos but entire visual identities — multiple angles, different outfits, varied settings — making traditional reverse image search ineffective.

The Solution

How DeepSight helps

Upload-time screening

Integrate DeepSight into your profile photo upload flow. Screen every photo at the point of upload, flagging or blocking AI-generated images before the profile goes live.

Low false positive rates

Our multi-signal approach minimizes false positives on professionally photographed portraits, beauty-filtered selfies, and other legitimate content that single-model detectors frequently misclassify.

Batch scanning for existing profiles

Scan your existing user base for AI-generated profile photos. Identify and flag suspicious profiles for review without disrupting the experience for genuine users.

Transparent user communication

When a photo is flagged, provide users with clear feedback. DeepSight's confidence-scored results enable nuanced responses: high-confidence detections trigger rejection, while borderline cases request verification.

Your Workflow

How it works

User uploads a profile photo to your platform

DeepSight API analyzes the image in real-time during upload

High-confidence AI detections are blocked or flagged automatically

Borderline cases are queued for human review with forensic context

Common Questions

Frequently asked

No. DeepSight distinguishes between AI-generated images and filtered photographs. Beauty filters, portrait mode, and professional retouching do not trigger false positives because the underlying image is still photographic in origin. Our confidence scoring accounts for post-processing.

See it in action

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

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