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SHIELD Tech Stack
Device-first fraud intelligence platform with persistent device identification
SHIELD operates a device identification and fraud detection platform, built on proprietary technology for tracking devices across applications and platforms. The stack is heavy on systems languages (C++, C, Go) alongside Python and data tools (MySQL, PostgreSQL, Redis, MongoDB), reflecting both real-time processing demands and analytics volume. Active pain points center on scaling ML models, detecting novel fraud patterns, and maintaining performance under load — all consistent with a platform handling high-velocity detection at global scale.
Tech Stack 43 technologies
Core StackMySQL C++ Python Go PostgreSQL Redis Tableau Adobe Illustrator Figma Canva After Effects Adobe Premiere Pro React MongoDB C Git Memcached Android SDK C/C++ Xcode CocoaPods Android Studio Gradle Fastlane Android Excel Qlik Sense SQL InDesign Photoshop+13 more
What SHIELD Is Building
◆Challenges
- Stop fraudulent activity
- Eliminate fake accounts
- Reducing fraud risk
- Detecting fraud patterns in large data sets
- Scaling machine learning models
- Optimizing performance of fraud detection system
- Proactive fraud detection
- New and unknown fraud threats
- Optimizing risk management strategies
- Staying ahead of fraud threats
▲Active Projects
- Poc implementation and onboarding
- Fraud detection solution r&d
- Demo customization
- Proactive fraud detection systems
- Ai-based alert systems
- New fraud detection methods
- Mobile sdks for android
- Case studies
- Press releases
- Employee engagement activities
Hiring Activity
20 roles · 8 in 30d
Department
Seniority
Notable leadership hires: Account Director
Company intelligence
