Matillion launched Maia in 2025 as an AI Data Automation platform centered on three integrated components: autonomous agents that handle pipeline maintenance, a context engine that captures business rules and standards, and an enterprise foundation layer with built-in governance and observability. The stack spans Python, Java, React, TypeScript, and multi-cloud infrastructure (AWS, GCP, Azure), with heavy investment in agentic tooling and CI/CD. Sales-led hiring velocity is accelerating—19 of 20 active roles posted in the last 30 days, 11 in sales alone—while engineering focuses on architecture (micro-frontends, design systems, gen AI) and automation, signaling a shift from maintenance-heavy workflows toward product-market expansion.
Matillion is a UK-based data automation platform that helps data teams move from pipeline maintenance to higher-value work. Maia, the flagship product, combines AI agents for repetitive pipeline tasks, a rules engine for governance and transparency, and enterprise-grade security and observability. The company serves mid-market and enterprise data teams building cloud data warehouses on platforms like Redshift, and operates across UK, US, India, and Australia. With 201–500 employees and active projects spanning agentic AI, micro-frontend architecture, and developer experience improvements, Matillion is scaling sales capacity while investing in platform depth.
Maia is Matillion's AI Data Automation platform introduced in 2025. It consists of autonomous AI agents that build and maintain data pipelines, a Context Engine that captures business rules and standards, and a Foundation layer providing security, governance, and observability for data products.
Matillion's stack includes Python, Java, TypeScript, React for frontend, multi-cloud infrastructure (AWS, GCP, Azure), Kubernetes, Kafka, PostgreSQL, MongoDB, and data warehouse integrations including Amazon Redshift, Oracle, and SQL Server.
Matillion'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.