Federal financial management, data and modernization services for VA programs
Trilogy Federal is an Arlington-based federal contractor whose stack pairs VistA with Apptio, Power Platform and the Microsoft BI suite, pointing to Veterans Affairs work spanning IT cost transparency, case workflows and reporting. Its one adopting signal, SQL Server Analysis Services, matches active projects to stand up an SSAS environment and migrate reports onto it. Hiring is accelerating with a senior-weighted, ops- and finance-leaning mix.
Trilogy Federal is a privately held professional services firm founded in 2009 and headquartered in Arlington, Virginia, with 51–200 employees. It serves federal government clients, with a particular focus on programs supporting Veterans. Its roots are in implementing, operating and modernizing financial management systems, and it has expanded into data and analytics, systems integration, healthcare transformation, benefits optimization, organizational change management and audit support. Delivery teams work across AWS and Azure, Oracle and SQL Server databases, and BI tools including Power BI, Tableau, MicroStrategy and Business Objects.
Trilogy Federal works with AWS, Azure, Azure Synapse and Data Factory, SQL Server (SSIS, SSAS, SSRS), Oracle and PL/SQL, Power BI, Power Platform, Tableau, Apptio, VistA, Jira, Jenkins and Selenium.
Current projects include enterprise workflow and case management apps, a clinical review workflow, a TBM cost transparency model, a VA program integrated master schedule and an SSAS reporting transition.
Trilogy Federal is headquartered in Arlington, Virginia, has 51–200 employees, and hires in the United States.
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Trilogy Federal'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.