Devis builds mission-critical software for federal, state, and local government—systems that span data entry to congressional interfaces across 80+ countries and every federal department. The stack is modern and deliberate: React/TypeScript frontend, GraphQL APIs, ASP.NET Core/.NET backend, Kubernetes orchestration on Azure, and PostgreSQL databases. Hiring 9 senior and mid-level engineers in the last 30 days signals either rapid project scaling or backlog clearance, likely driven by active modernization work: legacy test suite migration to Playwright, cloud data migration, and NIST compliance hardening.
Devis is a federal-focused IT consulting firm based in Arlington, VA, with 51–200 employees. The company delivers custom software, web portals, databases, and training to federal agencies, state governments, and international development organizations. Operations span more than 80 countries, and Devis-built systems are used by clerks, managers, and congressional staff. The practice emphasizes open standards, open-source tooling, and selecting technology matched to each project's constraints. Current work includes committee portal platforms, case handling workflows, intake systems, and low-code application development for transportation agencies.
Devis uses React and TypeScript on the frontend, ASP.NET Core and C# on the backend, PostgreSQL for databases, GraphQL for APIs, and Kubernetes with Azure DevOps for orchestration and CI/CD.
Current projects include committee portal platforms with GraphQL APIs, case handling and intake workflows, low-code application development for federal agencies, and migration of legacy test suites to Playwright and cloud data platforms.
Devis'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.