Custom software and AI/IoT solutions for financial services and defense sectors
Vooban is a 51–200-person custom software shop founded in 2011, now layering AI and data capabilities onto core .NET and cloud infrastructure. The hiring mix—heavily weighted toward senior and lead engineers—paired with active projects in LLM extraction, computer vision QC, and IoT sorting, signals a shift from traditional services delivery toward AI-augmented product work. Pain points around spec-to-production cycle time and modernization of legacy systems suggest the org is trying to escape low-margin consulting patterns.
Notable leadership hires: Tech Lead
Vooban delivers custom software, systems architecture, and AI-powered applications to financial services, insurance, and defense clients, primarily in Canada. The technical foundation is .NET, cloud platforms (Azure, AWS, GCP), and modern web stacks (React, TypeScript). Current project work spans LLM-based document extraction, computer vision quality automation, and IoT visual sorting—verticals typically demand high uptime and regulatory compliance. The org operates out of Québec and is currently accelerating headcount, with 12 roles posted in the last 30 days.
Core: .NET, .NET Core, C#, ASP.NET. Frontend: React, React Native, TypeScript, JavaScript. Data/infrastructure: PostgreSQL, MongoDB, SQL Server, Elasticsearch, Docker, Kubernetes, Azure, AWS, GCP. Also: Python, Swift, Objective-C for specialized work.
LLM-based data extraction from emails/PDFs, computer vision quality control automation, IoT visual sorting, legacy system modernization, and executive/account planning infrastructure. Also executing SEO and content strategy initiatives.
Vooban'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.