Technical staffing and custom IT solutions for regulated industries
Theoris is a staffing and systems integrator serving regulated and mission-critical sectors, built on Java, Spring Boot, and Angular with heavy reliance on Oracle, SQL Server, and AWS infrastructure. Active projects signal a shift toward automation and AI: the firm is building Claude AI connectors, developing automated data pipelines, and investing in observability tooling (Dynatrace, performance profiling) — indicating internal scaling challenges around data extraction, database bottlenecks, and peak-volume readiness that mirror the pain points they're solving for clients.
Theoris, founded in 1984 and based in Indianapolis, is a privately held consulting firm with 201–500 employees serving clients across the United States in regulated and high-impact industries. The firm operates on two legs: technical staffing (contract and direct-hire talent in IT, engineering, quality assurance, and leadership roles) and custom systems delivery (application development, data and analytics, Scrum teams, and project leadership). Their stack centers on enterprise Java, .NET, and web frameworks (Angular, React), with integration into legacy systems (SAP, Oracle) and modern cloud infrastructure (AWS, Kubernetes). They support clients through full project lifecycle: planning, development, testing, and deployment.
Java, Spring Boot, Angular, React, Oracle, SQL Server, AWS, Kubernetes, Jenkins, and Jira. Also integrates SAP, Veeva, and Oracle Primavera P6 for enterprise clients.
Indianapolis, Indiana. The firm has been operating since 1984 and maintains national reach, currently hiring only in the United States.
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Theoris'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.