Cloud platform for government tax collection, e-payments, and financial auctions
Grant Street Group operates mission-critical payment and tax infrastructure serving thousands of U.S. government entities. The tech stack reflects a mature, polyglot backend (Java, C++, Python, Go) paired with modern frontend tooling (Vue, React, TypeScript), suggesting deep legacy integration work alongside incremental modernization. Active hiring leans engineering-heavy (6 of 11 roles), concentrated in mid and senior levels, while pain-point data reveals heavy lifting around legacy tax data conversion and revenue analytics — indicating they're scaling both platform capacity and GTM instrumentation.
Grant Street Group builds cloud-based software for government agencies managing tax collection, e-payment processing, and financial auctions. The company serves over 6,800 government and financial entities across the U.S., processing over $20 billion in annual payment volume through PaymentExpress and handling two-thirds of Florida's property tax collection through TaxSys. Founded in 1997 and based in Pittsburgh, the 201–500 person organization is privately held. Core products span tax billing systems (TaxSys), vehicle and vessel registration renewals (RenewExpress), payment processing (PaymentExpress), and a financial auction marketplace that has facilitated over $13 trillion in transactions. Sales are RFP-driven with long cycles typical of government procurement.
Backend: Java, C++, Python, Go, Ruby, Perl. Frontend: JavaScript, Vue, React, TypeScript. Infrastructure: PostgreSQL, MySQL, Exasol, RabbitMQ, Apache NiFi, Ubuntu, OpenVPN. Payment: Stripe, Ingenico, Verifone terminals.
Primary projects: TaxSys client migration, legacy tax data reverse-engineering and conversion, scalable analytics dashboards, predictive forecasting models, pipeline health visibility, expanding government client footprint, and marketing measurement infrastructure.
Grant Street Group'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.