Xelix sells an AI platform that audits accounts payable for payment errors and fraud, automates supplier statement reconciliation and supports AP helpdesk work. Its stack is AWS-native: Python/Django on ECS, Lambda and Aurora, provisioned with Terraform, with a React/TypeScript front end. Hiring is accelerating and splits between engineering and sales, with a Frontend Lead search and job-post focus on uptime, CI/CD and productionizing AI for AP.
Notable leadership hires: Frontend Lead
Xelix is a privately held software company founded in 2018 and headquartered in London, England, with 51–200 employees. It builds an accounts payable control platform for enterprise finance teams that connects to existing ERP and finance systems. Core capabilities include duplicate payment and fraud detection, statement reconciliation, AP helpdesk automation and spend analytics. Customer onboarding runs through enterprise implementation projects, and the go-to-market team works in HubSpot and Gong. Current hiring is concentrated in the United Kingdom.
Xelix runs on AWS (ECS, Lambda, Aurora, RDS, CloudWatch, Route 53) with Terraform and Jenkins. The backend uses Python, Django, Flask and PostgreSQL, and the frontend uses React, Redux, RTK Query and TypeScript.
Yes. Engineering is Xelix's largest hiring area, followed closely by sales, with a Frontend Lead role open. Hiring is accelerating, is mostly senior-level and is based in the United Kingdom.
Xelix is building production AI systems for accounts payable, implementing its platform for enterprise customers, expanding its observability stack, improving CI/CD pipelines and developing a solution consulting playbook.
Other companies in the same industry, closest in size
Xelix'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.
