Enterprise software and data platform services for Oracle and SAP environments
NITYA is a 51–200-person IT services firm built around Oracle and SAP implementations, now shifting focus toward data modernization. The stack reveals a classical enterprise-to-cloud posture: Oracle, SAP, SQL Server, and VMware anchoring legacy work, while Kafka, Docker, Kubernetes, and AWS signal emerging data-platform and cloud-native capabilities. Active projects span hands-off file transfer, SAP data foundations, and agentic AI use cases—suggesting a move from pure implementation services toward managed data operations and analytics platforms.
Notable leadership hires: Oracle PL/SQL Technical Lead
NITYA Software Solutions is a Fremont-based IT services and consulting firm founded in 2005, operating across software development, enterprise solutions, ERP implementation, and IT consulting. The company serves mid-market and enterprise clients globally, with particular depth in Oracle Applications and SAP deployments. Current work spans custom software development, cloud migrations, and data platform construction; pain-point focus on manual file transfer, data quality, and legacy system modernization reflects a customer base mid-transition from on-premise to cloud infrastructure.
NITYA specializes in Oracle Applications and SAP implementations. The tech stack includes Oracle PL/SQL, SAP Business Data Cloud, and SAP Master Data Governance, alongside enterprise infrastructure (Salesforce, VMware, Cisco).
AWS is the primary cloud platform in the stack. Deployment and orchestration rely on Docker, Kubernetes, and Terraform, with Jenkins and Maven for CI/CD.
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NITYA Software Solutions 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.