Booking made → ID and selfie captured → Face matched to ID → Room key or boarding pass issued
Every step passes on process. None tested whether the face was real.
Travel and hospitality / NeuroVerify
Deepfake Detection API for Travel and Hospitality
Hotels, airlines and travel platforms are moving check-in, loyalty access and guest verification to selfies and video. Attackers use synthetic faces and swapped video to hijack bookings and loyalty accounts. NeuroVerify checks that media and returns one risk score with signal-level evidence.
It fits the selfie or face-capture step in your app or kiosk, with one API call and no new step for the guest.
NeuroVerify does not read passports or ID documents, check watchlists or approve a stay; it adds authenticity evidence to your own policy.
Powered byNeuroVerifyExplore the product
- #1 of 36on the public VendorBench-100
- <200 msp95 on eligible image requests
- 6 → 1six checks, one unified score
- 0new steps for your customer
The gap
Contactless travel put a face where a person used to be.
Digital check-in, mobile keys, self-service kiosks and biometric boarding all replace a staff member looking at a guest. A selfie or face capture now stands in for the front-desk glance. Booking platforms and loyalty programmes apply the same logic to account access and recovery.
Travel is also a fast, high-volume, cross-border business. Guests are strangers by design, identity documents come from many countries, and decisions often need to happen in seconds.
Where the current checks stop
Document capture shows a document was presented. It does not show who is holding it.
Selfie matching shows a resemblance, not that the selfie was captured live from that person.
Basic liveness is mostly built for physical spoofs, so injected video and face swaps are outside its design.
Remote and partner channels such as online travel agents, kiosks and third-party apps capture media on devices you do not control.
The same gap applies to loyalty accounts, where points and stored payment methods have real value.
Threats
How synthetic media is used against travel businesses
These are attack techniques, not claims about any company. Each turns a fake face into access to a booking, a room or an account.
01
Synthetic selfie at digital check-in
A generated face is matched against a stolen or fabricated ID photo to obtain a room key or boarding access.
02
Face swap on video verification
A real-time swap lets an attacker pass a video identity check as the booking holder.
03
Injected feed on a kiosk or app
A virtual camera supplies prepared footage so the platform records a clean capture with no real person present.
04
Loyalty account takeover via face recovery
A synthetic face or cloned voice is used to reset access and drain points or stored payment methods.
05
Fraudulent host or supplier onboarding
On marketplaces, a fake host or operator verifies with a synthetic identity to list properties or take deposits.
06
Chargeback and no-show manipulation
Manipulated selfie or video evidence is used to dispute a stay or deny an arrival.
Guest data is sensitive and often crosses borders. GDPR and similar laws shape how biometric and facial data is handled; see GDPR, biometrics and authenticity analysis.
NeuroVerify supports your controls with evidence, and your policy and legal review decide how it is used.
Where NeuroVerify fits
Authenticity evidence at the guest and account step
NeuroVerify sits after your app, kiosk or web flow captures a face image, video or voice sample, and before your policy issues a key, boarding access or account recovery.
Booking → ID and selfie → Face match → Key or pass issued
No authenticity signal for the face.
Booking → ID and selfie → NeuroVerify risk score → Face match → Key or pass issued or reviewed
One call added. Guests see the same flow.
Six signals, one request
- Visual Safety Screening - Live Presence Verification - Face Manipulation Detection - AI Generative Model Analysis - AI Pixel-Level Manipulation - AI Content Compliance
Built for scale
Native mobile SDKs, backend SDKs and a REST API fit apps, kiosks and partner integrations. Deployment ranges from managed cloud to private cloud and on-premises. See deployment and digital onboarding.
NeuroVerify Unified Trust LayerSix parallel analysis layers
- Visual Safety Screening
- Live Presence Verification
- Face Manipulation Detection
- AI Generative Model Analysis
- AI Pixel-Level Manipulation
- AI Content Compliance
Capture the guest face as usual
Keep your selfie or video step in the app, kiosk or partner flow.
Send it to NeuroVerify
Post the media from your backend, mobile SDK or REST API in one request.
Read the unified score
Receive one risk score with signal-level evidence to store on the guest or account record.
Apply your policy
Allow check-in, send to front-desk or fraud review, or step up verification, using your own thresholds.
What you get
What it changes for travel and hospitality teams
Keep contactless journeys, add trust
Guests keep the speed of digital check-in while synthetic faces get flagged before a key or pass is issued.
Protect loyalty and booking accounts
Screening face and voice media at recovery stops attackers from converting points and stored cards into cash.
Cut manual review at the desk
Signal-level evidence lets staff or fraud teams focus on flagged cases rather than checking every guest.
Works across channels and partners
One API covers app, kiosk and web, whether you run the capture or a partner does.
Deployment that fits data rules
Managed cloud, private cloud, container, on-premises and air-gapped options suit cross-border data requirements.
Questions
What teams ask before they integrate.
Do we still need a separate liveness check?
NeuroVerify is not meant to sit next to a liveness product as a second vendor. Live Presence Verification is one of the six signals in the same request, alongside Face Manipulation Detection, AI Generative Model Analysis, AI Pixel-Level Manipulation, Visual Safety Screening and AI Content Compliance. It checks guest selfies, video and audio for deepfakes and manipulation beyond liveness.
Standalone liveness is usually built around physical presentation: a printed photo, a mask, a screen held to a lens. It was not designed to tell you whether the face or voice inside a stream was generated or injected. Many teams keep their existing liveness vendor during evaluation and compare outcomes on their own media before deciding what to retire. See deepfake detection vs liveness detection.
How do we integrate it?
Call it after the guest face capture and before the key, pass or account change is approved. Send the media you already capture to one REST endpoint, or use a native mobile SDK (Android/Kotlin, iOS/Swift, Flutter) or a backend SDK (Python, TypeScript/Node.js, Go, Java). An MCP server is available for AI agents.
Integration is two lines of code in the common case, and teams can go live in under 24 hours. Your end users see no new step.
Does it read passports or ID documents?
No. NeuroVerify checks face images, video and audio, not documents. Keep your passport and ID checks; NeuroVerify protects the selfie and face-match step that sits beside them.
Can it work offline or on a kiosk?
Kiosks can send media to the API like any app. Where connectivity or data rules require it, NeuroVerify can be deployed in a private cloud, container, on premises or air-gapped. See deployment.
How is our data handled?
Neural Defend analyses the media you send and returns a risk score with signal-level evidence. Consent, retention and residency stay under your policy. Neural Defend holds ISO/IEC 27001, ISO/IEC 27701, ISO/IEC 42001 and SOC 2 Type II certifications.
Read the product data handling page and the trust centre for specifics, and ask us for the details your security review needs.
Is it fast enough for a live journey?
NeuroVerify returns in under 200 ms p95 on eligible image requests under defined test conditions. The methodology is available on request.
Latency for video and audio depends on length and deployment, so we measure it with you on your own traffic during evaluation.
Can we test it on our own media?
Yes, and it is the only test that counts. Published benchmarks do not reflect your devices, codecs or compression. Neural Defend ranks first of 36 systems on VendorBench-100 (MCC 0.876 against 0.646 for the next-best vendor), but your guest check-in media is the better yardstick.
Bring representative genuine and suspected-fake samples and your current decision states, and we will run them through the API with you.
Evaluate NeuroVerify
Test it on your own check-in and recovery media.
Send genuine and suspected-fake guest selfies and video through NeuroVerify. We will show the scores and signals and help set thresholds that suit your front desk and fraud team.