Hokentech

Hokentech

TrustWatch (by Hokentech) is an AI-driven application that authenticates luxury watches from a single photo, aimed at collectors, retailers, and repair shops to quickly identify counterfeit timepieces.

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Paid Enterprise 70/100
#31 in AI Detection (31 tools)
Added 5 months ago
30059 directory views this week

Quick Overview

Best for: AI Detection

What it does

AI Detection software for decision-makers comparing workflow fit and alternatives.

Best fit

AI Detection

Pricing snapshot

Paid from €12/month

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Hokentech

TrustWatch is an AI-powered watch authentication system built to help enthusiasts, retailers, jewelers and repair shops verify the authenticity of luxury watches quickly and affordably. Users upload photos (typically of the dial) from a smartphone, tablet or PC; the app analyzes watch details with a proprietary TensorFlow-based machine learning model and returns a simple authenticity score. The product emphasizes ease-of-use, broad brand/model coverage and continuous learning via dataset expansion and user contributions.

TrustWatch (by Hokentech) is an AI-driven application that authenticates luxury watches from a single photo, aimed at collectors, retailers, and repair shops to quickly identify counterfeit timepieces.

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Key Features

AI-driven authentication

Proprietary AI model (trained with supervised learning/TensorFlow) analyzes watch details—logo, dial, hands, markers, case, bezel, crown—to classify authenticity.

Single-photo scan

Authenticate a watch by uploading or taking a single photo of the dial; the system returns a result in seconds.

Broad brand & model coverage

Supports dozens of luxury brands and hundreds of models (site references over 500 models and lists brands such as Rolex, Richard Mille, IWC, Omega, Patek Philippe, Panerai, Audemars Piguet, TAG Heuer).

Fast results

Typical analysis completes in a few seconds; workflow described as upload (1 minute), AI check (3 seconds), share result (1 minute).

Continuous learning & contributions

Model improves through dataset expansion; users may contribute photos of known fakes to help train and refine the system.

Cross-platform access

Service is accessible from smartphones, tablets and PCs; a mobile app for Android and iOS is planned.

Unlimited scans (Ultimate plan)

Paid plan offers unlimited scans, uploads and brand checks.

Payment gateway support

Accepts major cards (Visa, Mastercard, American Express).

Tutorials and demo

Site provides a demo and tutorial pages explaining how to take photos and use the tool.

Pricing

TrustWatch Ultimate

€12/month
  • Unlimited watch scans
  • Unlimited watch uploads
  • Unlimited watch brand checks
  • Access to models (site references over 500 different models)

Use Cases

Individual buyers & collectors

Quickly check a watch before purchase (online or in-person) to avoid buying counterfeits.

Jewelers & retail stores

Speed up in-store authentication workflows to verify inventory or incoming trade-ins without waiting for an external expert.

Repair shops

Use the tool as an initial authenticity check before accepting or repairing luxury watches.

Online sellers / marketplaces

Provide added trust signals for listings by pre-checking items prior to sale (implied use case from buyer/trader workflow).

Integrations

Visa / Mastercard / American Express

Payment gateway support for subscription purchases using major credit cards.

TensorFlow (ML framework)

Uses TensorFlow in the model training/process pipeline to build and run the supervised learning model.

Benefits

Avoid expensive mistakes — helps prevent purchasing counterfeit watches.
Saves time and money compared to traveling to and paying external experts.
Fast, easy-to-understand results from a single photo in seconds.
Broad coverage of popular luxury brands and hundreds of models.
Continuous improvement through dataset contributions from users.

Limitations

Not 100% accurate — reported accuracy is 96.20%; users should confirm with a professional for final verification.
Possible false positives for new models or models not present in the dataset yet.
Requires clear, well-lit photos (reflections or poor images reduce reliability).
No public API documentation available on the site for external automation (see API section).
Site enforces no-refund policy for subscription cancellations (changes apply next billing cycle).

Frequently Asked Questions

What is the TrustWatch system?
TrustWatch is an AI system that determines the authenticity of luxury watches by analyzing photos with a trained model to classify watches as genuine or counterfeit.
How does TrustWatch work?
Users upload photos (typically of the dial). Images are analyzed by a TensorFlow-based supervised learning model trained on labeled examples to recognize and verify watch features.
How accurate is the model?
The site reports a K-Fold Cross Validation accuracy of 0.962 (96.20%). The company notes the system is not perfect and recommends additional professional checks when necessary.
Can I use TrustWatch on any device?
Yes — the service can be used from a smartphone, tablet or PC. Mobile apps for Android and iOS are planned for future release.
Where can I find a tutorial or demo?
The website provides a tutorial and a demo link showing how to use the tool and its features.
How do I contact support?
Support is available via email at [email protected] for questions about the authentication system or related topics.
How do I cancel or downgrade my subscription?
You can cancel or change your subscription from the account page (log in with the same email used to register). Changes take effect at the start of the next billing cycle; the site states no refunds are applied.
How can I contribute data or help improve the system?
You can send photos of known fake watches (front, rear, dial, bezel, etc.) to [email protected] to help expand the dataset and improve model accuracy.

Getting Started

  1. 1 Step 1: Open TrustWatch on your device and sign in or register (use the same email you will manage subscriptions with).
  2. 2 Step 2: Upload or take a clear photo of the watch dial (good lighting, avoid reflections) for best accuracy.
  3. 3 Step 3: Let the AI analyze the image (results typically in a few seconds) and save or screenshot the result to share.

Support

email

Primary support: [email protected] for questions, contributions and support requests.

docs

On-site tutorial and demo pages explain how to take photos and use the authentication features.

roadmap

Public roadmap link is available on the site to track progress and upcoming features.

API

Available: No

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