Enterprise software delivery and GenAI integration for large organizations
Zenitech is a UK-based delivery firm built around partnerships with enterprise clients on high-stakes digital transformation projects. Their tech stack—Python, .NET, Kubernetes, Azure, AWS—reflects a polyglot, cloud-native engineering culture. Active projects cluster around GenAI: RAG implementations, LLM integration into business planning workflows, and conversational interfaces. The hiring profile is senior-heavy and accelerating in Eastern Europe (Hungary, Lithuania, Romania), paired with internal pain points around inference optimization and model observability—clear signals they're moving from pure delivery services toward building and owning AI-augmented products.
Zenitech designs, delivers, and implements custom software for enterprise clients seeking digital transformation. Founded in 2015, the firm operates across software engineering, product development, cloud infrastructure, UX design, and quality assurance, with 201–500 employees based in London. Recent work includes national lottery applications and customer-service digitalization for major financial institutions. The company's model centers on embedded partnership: engineers and designers embed in client organizations rather than hand off deliverables. Current project velocity shows a pivot toward GenAI capabilities—building LLM-powered planning systems, RAG pipelines, and real-time conversational interfaces—alongside traditional modernization work (e.g., smart motorway sign control systems).
Python, C#, .NET Core, ASP.NET Core, Angular, TypeScript, Docker, Kubernetes, SQL Server, AWS, Azure, GCP, and RabbitMQ/SQS for messaging. They're actively adopting RAG for AI applications.
Enterprise software delivery, cloud migration, and—increasingly—GenAI: LLM integration into business planning, RAG implementations, conversational interfaces, and legacy system modernization (e.g., motorway sign networks).
Zenitech'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.