Verify every travel document in seconds, not minutes.
VeriScanx is a computer-vision pipeline that inspects passports and ID documents for tampering, cross-checks passenger details against live government and international records, catches duplicate or blacklisted identities, and hands the counter officer one clear risk score — before the traveler has finished stepping up to the desk.
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Manual document checks don't scale, and forged documents don't announce themselves.
Immigration counters and airport kiosks still lean on a trained eye and a UV lamp. That's slow at peak hours, inconsistent across shifts, and easy to beat with a well-made forgery, a photo-swapped passport, or a document that's already on a blacklist under a different alias.
Throughput bottleneck
Peak-hour queues grow because each document needs a manual look, even when 90%+ are genuine.
Inconsistent scrutiny
Fatigue, shift changes, and lighting mean the same forged page can pass one officer and not another.
Siloed watchlists
National blacklists, Interpol-style alerts, and prior-scan history rarely get cross-checked in real time.
One scan, six checks, one decision.
Every document that comes through the kiosk or counter scanner moves through the same pipeline, so the outcome is repeatable regardless of who's on shift.
Capture & upload
Kiosk camera, counter scanner, or mobile app ingests the document image and, where available, the NFC chip data.
OCR & MRZ parsing
Extracts the visual fields and machine-readable zone, then validates the MRZ checksum digits.
Image forensics
Error-level analysis and print-pattern checks surface splicing, re-prints, and photo substitution.
Database cross-check
Queries issuing-authority records, the national blacklist, and international watchlists in real time.
Identity resolution
Face-matches the document photo and searches prior scans for duplicate or multiple identities.
Risk scoring
A weighted, explainable 0–100 score routes the traveler to clear, secondary review, or escalation.
Built around the ways travel documents actually get faked.
Tamper & forgery detection
Error-level analysis and font/kerning consistency flag edited regions and photo swaps.
MRZ & field validation
Checksum digits and cross-field consistency (name, DOB, document number) are verified automatically.
Blacklist & watchlist matching
Real-time lookup against national blacklists and international alert lists on every scan.
Multiple-identity detection
Searches prior scans for the same face or biographic details filed under a different name.
Real-time, explainable risk score
A weighted 0–100 score with a visible breakdown, not a black-box yes/no.
Officer dashboard & audit trail
Every scan, decision, and override is logged for review and analytics.
Five layers, one pipeline.
What we're targeting for the pilot.
These are design targets for the prototype, not measured production figures — they're what the pipeline above is architected to hit.
Built for SIH 2026.
See it catch a forgery, live in your browser.
No install, no account — upload a document or try a fictional specimen and watch the real tamper-detection pass run in seconds.
Run a document through the pipeline.
Upload any ID-style image, or try a fictional specimen document below. The image-forensics panel runs a real error-level-analysis pass on your image in the browser; OCR extraction, MRZ parsing and database lookups are simulated against a small demo dataset — clearly marked below, no real government systems are queried.
Drop a document image, or click to upload
JPG or PNG · processed entirely in your browser
No submit button — results update live as you type. Try document number 118334029917 (on the demo blacklist), name Farid Osei with DOB 1988-03-11 (a duplicate already in the demo scan history), or document number 583104927615 with name Siddharth More and DOB 1992-05-03 (a real record in the national registry).
Today at Terminal 2, Counter 4–9
Scan volume — last 14 days
Scans by risk band
Recent scans
| Time | Traveler | Document | Country | Risk | Status |
|---|
Identity graph THIS SESSION
Every identity (name + DOB) and document number scanned this session, and how they connect. A document linked to more than one identity, or an identity linked to more than one document, is highlighted as a conflict.
Top flag reasons — last 14 days
Identity graph — conflicts detected
Mutation detector THIS SESSION
Looks for near-duplicate identities across this session's scans that an exact-match check would miss — a spelling variant of the same name, or a date-of-birth off by a few days — a common pattern when someone submits slightly altered details across applications. Each pair gets a stability score: lower means less consistent, more likely the same person under drifted details.