AI and computer-vision authentication for luxury goods and sneakers
Entrupy authenticates high-value physical goods using computer vision and microscopy, selling to resellers, pawn shops and marketplaces. Its hiring tilts toward product and operations rather than core engineering, and project signals point to category expansion into watches, branded jewelry and apparel, backed by ML training-data labeling. Hiring spans Japan, India, the UAE, Italy, Indonesia, China and the UK, signaling a push for consistent authentication across regions.
Entrupy is a privately held company headquartered in New York, founded in 2012, with 51–200 employees. It provides an AI-driven authentication service for luxury handbags, accessories and sneakers, combining patented computer vision with microscopy hardware. Customers include secondary resellers, pawn shops, marketplaces and enterprises. The engineering stack runs on Python with Flask and FastAPI on AWS, plus Android apps built in Kotlin. Commercial and finance operations rely on HubSpot, Salesforce, Chargebee, Stripe, Zuora and NetSuite.
Entrupy uses Python, Flask, FastAPI, AWS, NoSQL, Android SDK and Kotlin for its product, with HubSpot, Salesforce, Chargebee, Stripe, Zuora and NetSuite for sales and billing.
Entrupy hires in the United States, Japan, India, the United Arab Emirates, Italy, Indonesia, China and the United Kingdom, with a focus on product and operations roles.
Entrupy is expanding authentication into watches, branded jewelry and apparel, building structured knowledge systems, real-time authentication monitoring and ML training data labeling.
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Entrupy's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.