Saltar al contenido
Verify
AI authenticity

Catch synthetic media before it lands in your workflow

Detect AI-generated images, faces, and video with continuously updated models trained on the latest generation tools and adversarial datasets.

  • GAN, diffusion, and face-swap detection
  • Trained against current open-source models
  • Per-region heatmap explainability
  • Standalone or wraps any verification flow
Get started
98.2%
AUC on red-team eval
40+
Generators evaluated
<400ms
Image analysis
98.2%
AUC on red-team eval
40+
Generators evaluated
<400ms
Image analysis
Q
Update cadence
Capabilities

Built for production-grade trust

Each capability ships with monitoring, audit trails, and a typed SDK. Composable — pick what you need, leave the rest.

Image authenticity

Detect diffusion and GAN-generated stills with calibrated probability scores.

Face manipulation

Spot face-swap, reenactment, and morphing attacks on uploaded portraits.

Adversarial robustness

Resilient to common adversarial augmentations like compression, crop, and re-encoding.

Explainability

Heatmaps localize which regions drove the synthetic verdict.

How it works

From integration to verified result

A consistent flow whether you call via SDK, REST API, or trigger via dashboard.

  1. 1

    Submit

    Send an image or video frame to the API.

  2. 2

    Analyze

    Models score against known generation patterns.

  3. 3

    Explain

    Receive a verdict, score, and heatmap.

  4. 4

    Route

    Approve, escalate, or block based on your policy.

Use cases

Where teams deploy this

Patterns we see across regulated industries and high-velocity marketplaces.

Onboarding selfies

Detect AI-generated faces submitted at sign-up.

User-generated content

Tag synthetic media before it’s amplified on your platform.

Trust & safety

Triage suspected non-consensual or impersonation media.

Integrate in minutes

Production-ready SDKs and a typed REST API

Drop into your stack with a single dependency. Typed responses, idempotency keys, and structured errors out of the box.

POST /v1/deepfake/scanhttp
POST /v1/deepfake/scan
Authorization: Bearer $VERIFY_API_KEY
Content-Type: application/json

{
  "imageUrl": "https://cdn.acme.com/uploads/avatar.jpg",
  "explain": true
}
FAQ

Frequently asked

Don't see your question? Reach out — we usually respond within a business day.

Ready to roll out deepfake detection?

Spin up a sandbox in minutes, or talk to our team about a tailored rollout for your compliance and volume requirements.

Start free
Related solutions