AI-driven invoice lifecycle and purchase-to-pay automation platform
Basware builds invoice automation and purchase-to-pay software for finance teams, now pushing AI deep into its core product. A Databricks-centric data stack (Delta Lake, Unity Catalog, MLflow) alongside Kubeflow and SageMaker points to a maturing MLOps practice, matching active projects on multi-model extraction and AI-native document capture. Hiring is accelerating and skews senior and engineering-heavy, with product and support close behind.
Notable leadership hires: Legal Project Lead
Basware, founded in 1985 and headquartered in Espoo, Finland, provides software for managing the full invoice lifecycle, including accounts payable automation, e-invoicing, procurement, and travel and expense management. Its customers are finance and procurement teams that need control and compliance across invoice transactions and supplier collaboration. The privately held company employs between 1,001 and 5,000 people. Its core platform runs on Java and Spring Boot with C# and Python, deployed across AWS and Azure. Hiring spans the United States, United Kingdom, India, Netherlands, France, and Romania.
Basware uses Java, Spring Boot, C#, and Python on AWS and Azure, with MongoDB, SQL Server, Oracle, and MySQL, plus Databricks, Delta Lake, MLflow, Kubeflow, and SageMaker for data and ML. Salesforce and HubSpot support go-to-market.
Basware is building a multi-model extraction architecture, an AI-native document capture solution, and an MLOps architecture, while integrating AI and LLMs into core product flows.
Basware hires in the United States, United Kingdom, India, Netherlands, France, and Romania, with an engineering-heavy, senior-skewed mix and accelerating hiring velocity.
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Basware'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.