Introduction
TrustWatch is an AI-driven system and upcoming mobile application that authenticates luxury watches from photographs. Built using supervised learning techniques (TensorFlow mentioned) and trained on thousands of real and counterfeit watch images, it analyzes key visual features — logo, dial, hands, markers, case, bezel, crown — and outputs a confidence score (K-Fold cross-validation accuracy reported as 0.962).
Key features:
- Photo-based authentication: upload or capture dial images via smartphone, tablet, or PC for fast analysis.
- Fast inference: results in seconds with a simple numeric confidence indicator.
- Broad brand & model coverage: supports 6+ major brands and over 400 models (claims >500 models in some sections).
- Continuous learning: users can contribute images to expand dataset and improve model accuracy.
- Web & future mobile apps: current web interface with planned iOS and Android releases.
- Subscription plan: “TrustWatch Ultimate” at €12/month offering unlimited scans, uploads, and brand access.
Use cases:
- Watch enthusiasts verifying purchases from classifieds or marketplaces before buying.
- Retailers and jewelers accelerating in-store authenticity checks.
- Repair shops screening incoming watches.
- Collectors building provenance records or sharing verification results.
Security & limitations:
- Not infallible: reported accuracy ~96.2%; recommends follow-up professional inspection for final verification.
- New/unseen models can produce false positives; dataset-dependent performance.
