Oracle and Microsoft stack consulting for enterprise modernization
Speridian is a consulting and managed-services firm built around Microsoft (Power Platform, Dynamics 365, Azure) and Oracle (Fusion, SOA, Siebel) implementations. The tech stack reveals a modernization play: heavy Power Platform adoption paired with cloud (AWS, Snowflake, Azure) and analytics (Power BI, Tableau, Looker), while pain points cluster around legacy ETL migration and manual process replacement. Hiring velocity is accelerating across product and healthcare verticals, with mid-to-senior technical leadership filling out delivery teams.
Speridian Technologies is a consulting and managed-services firm serving mid-market and public-sector enterprises across digital transformation, cloud migration, and business process automation. Founded in 2003 and headquartered in Albuquerque, the firm spans 1,001–5,000 employees. Core service lines include advisory, implementation, and managed services across AI, automation, cloud platforms, analytics, and enterprise software (Oracle, Microsoft Dynamics). Notable current work includes behavioral health system transformations, statewide DHCS platform rollouts, and large-scale technology modernizations for government agencies and healthcare enterprises. The firm operates across the United States.
Primary: Microsoft Power Platform (Power Apps, Power Automate, Dynamics 365, Dataverse), Python, Java, .NET, SQL Server, Azure, AWS, Snowflake. Analytics: Power BI, Tableau, Looker. Frontend: Angular, ASP.NET Core, HTML5, JavaScript. Also Oracle Siebel, Fusion, SOA from legacy and ongoing customer engagements.
Active projects include behavioral health platform transformations, statewide public-sector DHCS rollouts, medical enterprise system modernization, Snowflake cloud implementations, Power Platform governance frameworks, and virtual agent development for task automation. Heavy focus on replacing legacy processes and migrating legacy ETL to cloud.
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Speridian Technologies'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.