●Fraud & risk teams
AI fraud detection for images, video and voice.
Detect AI-generated images, face-swapped video and cloned voices inside your fraud stack. Structured results, an audit trail, built for enterprise volume.
●Platform
Detect it. Explain it. Act on it.
Every scan returns the same three things: a result, the signals that produced it, and a decision you can route on.
01
Detect
Every file is scanned by independent models for images, video and faces, in the web tool, the extension or by API.
3 / 4 signals corroborateCalibrated likelihood
02
Explain
See which signals fired and how strongly. No single model decides; every result comes with its reasons.
Rule: likelihood ≥ 0.85 → Flag<3s
03
Route
Branch your workflow on the result. Clean items pass, flags go to review with a full audit trail.
●The problem
Fraud has gone generative.
AI-generated damage photos in claims. Synthetic identity documents in KYC. Deepfake video calls authorising wire transfers. Existing fraud stacks were not built for this.
●What we catch
What gets flagged.
Flagged at the point of submission, before it reaches a reviewer.
01
AI-generated selfies
Generated faces submitted in onboarding and account recovery.
02
Face-swapped liveness
Replacement and reenactment in recorded liveness checks and video calls.
03
Synthetic ID documents
Generated or edited identity documents in KYC flows.
04
Voice clones
Cloned voices used to authorise transfers or take over accounts.
05
AI-generated claim evidence
Damage and refund photos created to trigger payouts.
06
Recycled media
The same image reused across accounts, including edited variants.
The pipeline
A detector for each kind of media.
Image, video and voice each have their own detector. Their findings come back as one clear answer you can act on.
Image
Diffusion, GAN and face-swap images from Midjourney, DALL·E, Stable Diffusion, Flux and Firefly.
LiveVideo
Face swaps across 32 frames and fully generated video from Runway, Kling, Veo and Pika.
LiveVoice
Cloned and synthesised speech in calls, notes and recordings.
LiveWhat you get
Each file is marked Pass, Flag or Review, with the likelihood, signals and audit ID behind it.
One answer●Use cases
Where it matters.
Detect synthetic ID documents, deepfake liveness video and AI-generated selfies in onboarding. Prevent account takeover with voice-clone detection.
Screen submitted damage photos and flag recycled images across accounts. Reduce SIU backlog.
Detect AI-generated refund photos and patterns across claims, fast enough for real-time screening.
Screen digital evidence for face swaps, voice clones and manipulated video, with audit documentation.
●How it works
From submission to decision.
Submit media
Images, video frames or audio via REST. Batch and webhooks for async.
Ensemble analysis
Pixel forensics, frequency analysis and provenance run in parallel.
Structured result
Likelihood 0–100, Pass / Flag / Review and an audit ID as JSON.
Route
Auto-approve clean items, send flags to review, keep the full audit log.
●Integration
Three ways in.
Start with the web app.
Scan in the web app or Chrome extension today. The REST API and MCP server for your AI agents are coming soon. Same detectors, same result, same audit trail.
Web app
AvailableUpload in the web app. Images, video and voice, up to 50 MB. Full results in seconds.
Chrome extension
AvailableScan any image or video from inside the tools your team already uses. No download, no upload.
API
SoonSingle scans, batch jobs and webhooks. Structured JSON with result, likelihood, signals and audit ID.
curl -X POST https://witness.vision/api/v1/detect \ -H "Authorization: Bearer $WITNESS_KEY" \ -H "Content-Type: application/json" \ -d '{"media_url": "https://…/kyc_selfie_liveness_0092.mp4"}' → 200 OK · 412ms result: ai_generated · 0.94
●Why Witness
Built to be checked.
We say what the system does, what it returns and where its limits are.
Detection built per signal
Specialized models per signal, so you get more coverage and fewer false positives than one classifier.
Reasons, not just a score
Every result shows the signals behind it and where in the file they fired.
Analysed, then gone
Media is never stored, shared or used for training.
Provenance, when it exists
Reads Content Credentials from capture device to current file.
●Pricing
Priced around your volume.
No minimums and no long-term contracts. Tell us your volume and we will quote within one business day.
Free
$0
- 20 image scans a month
- 2 min video/voice total
- Full heatmaps
- Generator attribution
- EXIF/C2PA/SynthID
- Web and Chrome extension
●Pro
$15 / month
- 1,000 image scans a month
- 15 min video + 10 min voice
- Everything in Free
- Faces and face-swap specialist
- Scan by URL: paste any link
- Email support
Enterprise
Custom
- Volume pricing
- Everything in Pro
- SSO and audit logs
- Dedicated support
- Custom SLA
- On-premise option
●Explore
One engine. Every surface.
The same detection, result and audit trail across every team that handles media.
Detection
AI image detector
Find out if an image was made by AI.
Explore →Detection
Face swap detection
Find out if the face in a photo or video has been replaced, reenacted or lip-synced.
Explore →Detection
C2PA checker
Read the Content Credentials inside an image or video: who signed it, what captured it, and every edit since.
Explore →Detection
AI video detector
Find out if a video was generated by AI or contains a face swap.
Explore →Product
Chrome extension
Scan media on any site, social feeds, news, claims portals, case files, and get a result in the side panel..
Explore →How does it work?
An ensemble of detection models checks different signals, generative fingerprints, frequency artefacts, metadata, combined into one likelihood and result, returned in under 3 seconds.
What volume can the API handle?
Standard plans support thousands of scans per day. Enterprise plans include dedicated infrastructure, custom SLAs and priority support.
How is it priced?
Usage-based, per scan. No minimums or long-term contracts. Tell us your volume and we will quote within one business day.