Sports equipment and apparel manufacturer modernizing legacy systems
Champro manufactures team sports equipment and apparel distributed through specialty retailers. The tech stack reveals a mid-market operations platform built on Microsoft (.NET Framework, Dynamics 365, SQL Server, Azure) with legacy dependencies (ASP.NET Web Forms, .NET 2.0) creating friction. Active projects center on modernizing to .NET 10 and Blazor while managing core operational challenges—on-time trim delivery, cost/quality alignment, and inventory control—suggesting the engineering effort is tightly coupled to product and supply-chain execution rather than standalone software development.
Champro is a privately held sports equipment and apparel manufacturer founded in 1987, headquartered in Bannockburn, IL, with 201–500 employees. The company distributes products through sports specialty retailers and focuses on team sports categories. Operations span product design (seasonal and trim development), sourcing and manufacturing, inventory management, and customer support. Recent hiring activity (7 open roles, 5 posted in the last 30 days) is concentrated in support and manufacturing functions, with emerging engineering headcount dedicated to modernizing internal systems.
Champro runs on Microsoft infrastructure: Dynamics 365 (ERP and supply chain), SQL Server and Oracle databases, Azure cloud, .NET Framework and ASP.NET Web Forms for applications. Supporting tools include NetSuite, PLM, Adobe Creative Suite, Jira, and Azure DevOps. The stack is currently migrating from legacy .NET 2.0 to .NET 10 and Blazor.
Primary projects include seasonal and trim development, product testing for collections, and a major technology initiative: migrating legacy functionalities to .NET 10 and building new Blazor server applications. The engineering roadmap is dominated by modernization of legacy systems.
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Champro'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.