Project-based ERP and CRM for government contractors and AEC firms
Unanet sells project-centric ERP and CRM to government contractors, AEC and professional services firms, running on Java, Tomcat and SQL Server Reporting Services across AWS and Azure with FedRAMP in the stack. Hiring is accelerating and skews senior toward support, consulting and product, while job posts center on data migration, client onboarding and churn risk, signaling that implementation capacity and data readiness for AI are current bottlenecks.
Unanet, founded in 1988 and headquartered in Dulles, VA, builds ERP and CRM software for project-driven organizations, primarily government contractors, architecture, engineering and construction firms, and professional services companies. Its product covers project accounting, resource planning, timesheets, expense reporting, billing, revenue recognition, budgeting and DCAA compliance. The privately held company employs 201–500 people and hires in the United States. Go-to-market runs on Salesforce, HubSpot and Demandbase, with Gainsight and ChurnZero supporting customer success.
Unanet's stack includes Java, TypeScript, Python, Tomcat, AWS, Azure, SQL Server Reporting Services and Power BI, with Playwright, Selenium, Katalon and JMeter for testing, plus Salesforce, HubSpot and Gainsight.
Job posts point to ERP implementations for AEC clients, GovCon integrated solution rollouts, AI-enabled Growth Studio workflows and integrations, and AI-assisted product development using multi-agent workflows.
Unanet is headquartered in Dulles, Virginia, United States, and currently hires in the US, with senior-heavy openings across support, consulting and product.
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Unanet'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.