Supply chain authentication and consumer engagement via mobile technology
Sproxil operates a fraud-detection and consumer-engagement platform deployed across manufacturing and brand protection use cases. The tech stack is enterprise Java/Node.js with containerized deployment (Docker, Kubernetes) on AWS/Azure/GCP, and active hiring across ops, engineering, and sales signals scaling. Current project load reveals expansion into AI-driven backend services, regulated-market compliance (EUDR, GS1 EPCIS), and a nascent healthcare vertical (clinical protocols, medical response validation), indicating a pivot beyond traditional anti-counterfeiting into supply chain governance and AI-assisted diagnostics.
Sproxil builds mobile-first solutions for supply chain transparency and product authentication, primarily deployed by multinational manufacturers and brands to combat counterfeiting and fraud. The platform combines a proprietary fraud-detection engine with consumer engagement capabilities, allowing brands to amplify awareness and optimize promotional spend while securing supply chains. Operating globally with teams across Africa, Asia, and North America, Sproxil serves clients across five continents and operates in over 100 countries. The company is ISO 9001 and ISO 27001 certified. Current hiring focus (ops-heavy, with engineering and sales roles) and active projects in regulated-market adoption and AI services suggest expansion into healthcare, clinical workflows, and compliance-heavy verticals such as EUDR traceability.
Java, Node.js, TypeScript, Spring Boot, NestJS, and Express.js on the backend; MySQL, PostgreSQL, and Oracle for data; Docker and Kubernetes for containerization; AWS, Azure, and GCP for cloud; GitLab CI/CD and Bitbucket Pipelines for deployment.
Current projects span AI backend infrastructure, EUDR compliance traceability, GS1 EPCIS adoption, clinical protocol development for a healthcare vertical, and structured product launches targeting regulated markets.
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Sproxil'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.