Our proprietary dataset brings together extensive collections of authentic and counterfeit examples across luxury brands. Built through professional resale operations, it connects detailed item photography with product context and review history—the foundation for models that understand the realities of resale.
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Authentic and counterfeit examples. Exposure to both helps our models learn the subtle differences that matter when assessing an item.
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Breadth across luxury brands. Our data spans different brand signatures, materials and construction details, alongside the wear and variation found in pre-owned inventory.
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Evidence beyond catalogue photography. Close-up images reveal textures, stitching, stamps and hardware that ordinary product listings rarely capture.
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A resource that is difficult to replicate. Access to physical items, detailed capture and operational review records takes sustained relationships and specialist work. That accumulated evidence is a lasting competitive advantage.
COMPOUNDING VISUAL INTELLIGENCE
01Operational imagesReal items, real capture conditions
02Review recordsHuman and model decisions retain context
03Vision modelsPatterns learned across items and brands
04Review loopHard cases improve future coverage
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PROPRIETARY DATASET COVERAGE
Authentic and counterfeit examples across 11 luxury brands.
Louis Vuitton
Chanel
Hermès
Gucci
Dior
Celine
Loewe
Balenciaga
Prada
Goyard
Coach
Dataset breadth informs our development. Available checks vary by brand, item type and deployment.
Intelligence built for resale
From visual detail to a clearer decision.
We turn specialized visual intelligence into practical support for the teams identifying, assessing and reviewing luxury inventory.
01 / HINBAN — VISUAL IDENTIFICATION
Find the right reference from a photograph.
Hinban compares an intake photo with a library of product references to find visually similar models. It narrows the search by brand and brings together distinct candidates, with the images and product details your team needs to compare them.
Move from an unfamiliar item to a focused shortlist. Compare shape, material, colour and hardware, then confirm the reference that fits.
02 / KANTEI — AUTHENTICITY INTELLIGENCE
Read the details that tell the fuller story.
Kantei guides staff through 7–10 capture locations, depending on the brand, with instructions and reference images for materials, stitching, stamps and hardware. Drawing on patterns learned from authentic and counterfeit examples, it combines evidence from multiple areas to support a more informed authenticity assessment.
Go beyond a single verdict: inspect location-level scores alongside the photographs, compare signals across the item, and keep uncertain cases on Hold for further review.
03 / REAL-WORLD EVALUATION
Test for the conditions your team encounters.
Our evaluations use real intake imagery and account for repeated records, missing catalogue references and variation across brands. This helps us understand where the system is useful and where coverage needs to improve.
Review performance in the context of your inventory and workflow, with clear boundaries around supported items and use cases.
04 / CONTROLLED IMPROVEMENT
Improve coverage with a clear reference point.
We evaluate retrieval updates against recorded versions of the reference library and search system. This lets us compare changes before release and trace which references informed a result.
Adopt new coverage through a controlled rollout, with the configuration and review process matched to your operation.
Engineering behind the workflow
Built for production.
Built on Google Cloud and Modal, our platform is designed to support growing teams, additional locations and changing intake volumes.
BUILT ON+
Visual models that examine the materials, markings and construction details of an item.
Model serving for image-based product retrieval, helping turn photographs into searchable visual representations.
APIs that connect product identification, authenticity assessment and the tools your team uses.
Cloud Functions
Background tasks that keep item processing and operational workflows moving.