Zaizi is a 51–200-person engineering firm in London built around AWS, Kubernetes, and polyglot backend (Java, Python, Go) — a tech stack shaped for container-first cloud migration and complex system integration. The hiring mix is engineering-heavy (11 of 15 active roles, mostly senior and lead level), concentrated entirely in the UK, signaling focus on deep technical delivery rather than sales expansion. Active projects center on defence tenders, predictive maintenance systems, and legacy-to-cloud transitions, while pain-point data reveals the core challenge: untangling slow consultancy workflows and complex dependencies in high-risk, heavily regulated environments.
Notable leadership hires: Engineering Lead
Zaizi designs and builds digital services for UK public-sector organisations, with particular depth in defence and government cloud infrastructure. The company was founded in 2007 and operates from London as a privately held consultancy. Core work spans cloud migration (AWS, Azure, GCP), system architecture, DevOps, and emerging AI/ML applications — particularly predictive maintenance for defence use cases. The product philosophy emphasizes security and user-centric design; the operational reality focuses on managing complexity: long project lifecycles, intricate dependencies, and the regulatory and technical lift of sovereign digital programmes.
Zaizi uses AWS, Kubernetes, Docker, and a polyglot backend: Java (Spring Boot), Python, Go, plus TypeScript/React on frontend. Testing relies on Jest, Cypress, and JUnit. Workflow engines include Camunda and Activiti.
Zaizi is focused on digital services for UK public sector, including AI-driven predictive maintenance for defence, cloud migrations from legacy hardware, and technical strategy for major defence tenders. Recent projects emphasize high-velocity delivery models and system integration.
Zaizi'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.