Engineering, construction, and staffing services across defense, energy, and industrial sectors
Day & Zimmermann operates a multi-service engineering and construction firm spanning defense contracting, power generation, staffing, and operations management across 900+ sites. The tech stack reveals dual operational modes: enterprise systems (SAP, Salesforce, SuccessFactors, Oracle Primavera) managing global logistics and workforce, paired with emerging AI tooling (Anthropic, OpenAI, PyTorch, TensorFlow, RAG) indicating active investment in generative AI and predictive analytics—likely targeting shop-floor efficiency, supply-chain visibility, and compliance risk detection in heavily regulated sectors like nuclear and federal contracting.
Day & Zimmermann is a privately held services firm founded in 1901, headquartered in Philadelphia with 10,000+ employees across construction, engineering, operations & maintenance, staffing, and security & defense divisions. The company generates approximately $3 billion in annual revenue and maintains a geographically distributed workforce spanning 900+ workplace locations in the United States. Core customer bases include energy utilities, nuclear facilities, defense contractors, and industrial manufacturers. Active projects center on automation, lean process improvement, supplier quality systems, and enhanced planning capabilities—reflecting a shift toward efficiency and risk reduction in complex, regulated project environments.
Enterprise backbone: SAP, Salesforce, SuccessFactors, Oracle Primavera, Power BI, Blackline. Operations/engineering: AutoCAD, Maximo, SCADA, Microsoft Project, Primavera P6. Emerging AI: OpenAI, Anthropic, PyTorch, TensorFlow, RAG, scikit-learn, XGBoost.
Quality deficiencies in manufacturing, shop-floor efficiency, managing nuclear and federal projects, supply-chain performance, inventory control, automation implementation, and compliance risk detection in complex regulated environments.
Day & Zimmermann'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.