ML-Powered Secure Code — Ticvic Case Study
Case Studies / Security
Security · Machine Learning

A code format QR can't counterfeit — from patent filing to three production apps.

GoHexana's patented hexagonal secure codes, engineered into production: on-device ML decoding that works offline.

3
Production apps
Patented
Technology
Offline
Decoding
The ClientGoHexana, Saudi Arabia — inventor of a patented hexagonal-pattern alternative to QR and barcodes.
01

The Challenge

QR codes are easy to spoof and limited in capacity. The patented format needed production-grade engineering.

Frame drops and decoder failures in early builds
ML model too heavy for low-end phones
No scalable path to decoder-as-a-service
02

What We Built

The full encode/decode product line — mobile apps, web portal, and service APIs.

Mobile encoder/decoder apps with on-device TensorFlow models
Web portal encoder with code lifecycle management (enable/disable)
Optimized ML pipeline for low-end device support
Decoder-as-a-service architecture on Kubernetes
03

The Stack

TensorFlowOpenCVFlutterReactFastAPIMongoDBKubernetesJenkins CI/CD
04

The Results

Numbers from production operation — not projections.

70%
Decoder success rate in Phase 1
3
Production apps shipped
1
Patented innovation industrialized
I have obtained IP for the innovation that I applied for 4 years ago... Today I am happy that the work is achieving good results.
Majid Badr AlqarniFounder, GoHexana
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