WhirlWind Technologies

Whirlwind Technologies is a data systems modernization firm. For fifteen years we’ve delivered in environments where the data underneath the organization has to be right, has to be defensible, and can’t go down. That discipline shapes how we scope, build, and hand off every engagement.

Our work spans four connected practices.

Data infrastructure modernization. We assess aging data warehouses, plan phased migrations to modern cloud environments, and deliver the pipelines, catalogs, and governance structures that keep the infrastructure trustworthy after we leave. Most engagements open with a two-to-three week assessment and a phased roadmap, with implementation optional and separately scoped.

Machine learning for fraud and anomaly detection. Production ML systems that flag anomalous transactions and behaviors at scale, built by engineers and statisticians working together rather than handed from a research team to a delivery team.

AI-assisted document and data extraction. Production pipelines combining OCR, vision-language models, human-in-the-loop review interfaces, and confidence-scored capture into relational stores. We have delivered these end-to-end across multi-language, multi-currency, and multi-tenant contexts, including block detection, side-by-side operator review tooling, and template handling per client entity.

Custom applications and platforms. Multi-tenant SaaS, ERP and payment integrations, healthcare and financial services platforms, marketplace and portal builds. Role-based access control, audit logging, and permission architecture are built in from day one rather than retrofitted.

We staff small cross-functional pods: data engineers, data architects, ML engineers, backend and front-end developers, business analysts, business process engineers, statisticians, and PhD researchers. Engagements are fixed-price and phase-gated, so clients can end at any phase without carrying dead weight. We work with clients worldwide.