AI-native capital planning platform for infrastructure and facilities owners
Aurigo builds AI-native software for capital program lifecycle management—planning through construction to operations. The tech stack reveals a modern, AI-forward architecture: Azure OpenAI, AWS Bedrock, LangChain, LangGraph, and CrewAI sit alongside enterprise standards (Oracle Primavera, SAP, Maximo), suggesting a strategy to embed generative AI into legacy capital-planning workflows. Hiring velocity is accelerating (30 roles in 30 days), but heavily weighted toward sales (10 roles) and away from engineering (6 roles)—a sales-led growth push against long procurement and complex government buying cycles.
Notable leadership hires: Compliance Lead, Growth Director
Aurigo provides capital program management software trusted by over 300 organizations managing more than $450 billion in capital programs across North America. The platform—Masterworks—spans planning, construction, and operations phases, and integrates project performance tracking, ROI analytics, and AI-powered risk assessment. The company serves infrastructure and facilities owners facing long sales cycles and procurement friction; it operates across the United States, India, Canada, South Africa, and India. Founded in 2003 with 501–1,000 employees, Aurigo is privately held and headquartered in Austin, Texas.
Aurigo uses Azure OpenAI, AWS Bedrock, LangChain, LangGraph, and CrewAI for AI; Oracle Primavera, SAP, and Maximo for enterprise systems; PostgreSQL and SQL Server for data; React and FastAPI for frontend/backend; Kubernetes for orchestration; and Salesforce, Outreach, and Pardot for go-to-market.
Active projects include enhancing the Masterworks platform, partner enablement, sales enablement programs, product launch readiness, AI platform narrative development, competitive intelligence, and organization design. Pain points include long procurement cycles, complex government buying, and lead qualification inefficiencies.
Aurigo Software Technologies'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.