IT staffing and custom application development for enterprise clients
Client Resources is a 25-year-old IT staffing and solutions firm headquartered in Omaha, serving mid-market and enterprise clients across public sector, healthcare, financial services, and manufacturing. The tech stack reveals a heavy Microsoft/cloud orientation (Power Platform, Azure) paired with open-source data tools (Airflow, Meltano, Spark), and active project work on enterprise data platforms and legacy modernization — signals a shift from pure staffing toward managed services and data infrastructure delivery. Senior-heavy hiring (9 of 15 open roles) in engineering and data underscores investment in solutions delivery over pure body shop staffing.
Client Resources provides IT staffing, custom application development, and managed services to enterprise and mid-market organizations. Founded in 1999 and woman-owned, the firm employs over 180 IT and business professionals. Core service areas include mobile app development (native and web), enterprise IT strategy, application integration (via MuleSoft), and managed application services. The company works across financial services, healthcare, manufacturing, retail, and public sector verticals, with particular emphasis on modernizing legacy systems and building enterprise data infrastructure. Pricing and engagement models span traditional staff augmentation through strategic solution delivery.
Primary: Microsoft stack (Power Apps, Power Automate, Power BI, Azure, Dataverse). Data layer: Python, Apache Airflow, Meltano, dbt, Kafka, RabbitMQ, Spark. Application: Java, .NET, JavaScript, Vue. Infrastructure: AWS, GCP, Terraform, Docker, Kubernetes. Replacing Snowflake.
Active projects include enterprise data access platforms, event streaming pipelines, AI/ML data infrastructure, legacy system modernization, financial reporting systems, custom application development, and loosely coupled enterprise-scale component architecture.
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Client Resources, Inc.'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.