Commodity trading and risk management platform modernizing with AI and cloud infrastructure
Quoreka operates a Java/Spring Boot-based commodity trading platform serving banks, brokers, and producers globally for over 40 years. The tech stack reveals active modernization: adopting LangChain, CrewAI, and AutoGen signals a pivot toward AI-driven capabilities (likely test case generation and automation), while concurrent Playwright/Selenium investment and a dedicated automation platform project suggest heavy testing and quality infrastructure work. Hiring skews senior (11 senior roles, 3 leads, 3 principals out of 18 open) with concentrated engineering demand (8 roles), indicating capability-building rather than headcount scaling.
Quoreka is a commodity trading software provider operating across major global financial institutions, brokerages, and trading houses. The platform integrates trading execution, risk management, and commodity data workflows, built on a legacy Java/Oracle/MySQL stack supplemented by modern cloud deployment (AWS, Azure, Kubernetes, Docker). Current operational focus spans cloud migration, test automation modernization, financial process automation, and emerging AI-powered analytics. The company operates across six hiring regions with most hiring concentrated in engineering and product functions, reflecting technology infrastructure as a core competitive lever.
Java, Spring Boot, Node.js, React, Angular, Oracle, MySQL, MongoDB, AWS, Azure, Kubernetes, Docker, Jenkins, and GitLab CI/CD. Currently adopting LangChain, CrewAI, and AutoGen for AI capabilities.
London, England. The company employs 201–500 people and is privately held.
Quoreka'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.