Cloud and AI by Industry

Where we work most

• Retail and e-commerce: real-time inventory across POS, ERP and online, BigQuery for sales and loyalty data, and product data that AI shopping agents can read.
• Financial services and FinTech: landing zones built for APRA CPS 234 and CPS 230, real-time fraud scoring, and AI that stays in Australia.
• Healthcare and life sciences: FHIR data platforms, de-identification on ingest, genomics pipelines and clinical document processing.
• SaaS and technology: multi-tenant platforms on Cloud Run and GKE, cost per tenant, migrations from AWS, and AI features inside your product.

Don’t see your industry here?

We wrote up those four because they’re what people ask about most. It’s not a list of who we’ll work with.

We’ve delivered across property and construction, education and training, startups, wholesale and distribution, telecommunications, professional services, not-for-profits, and heavy industry. Different compliance regimes, different vocabularies, very similar engineering.

Why the sector matters less than you’d think

Under the domain language, the problems repeat. A hospital predicting emergency department demand and a retailer forecasting Tuesday’s stock movement are running the same time-series model against different columns. A bank proving who touched a customer record and a construction firm proving who signed off a site inspection need the same immutable audit trail. Migrating a mainframe and migrating an on-premise ERP both come down to strangling a monolith without a weekend outage.

So when someone asks whether we’ve worked in their industry, the more useful question is usually whether we’ve solved their shape of problem. Those shapes are: get off AWS, Azure or a data centre without downtime. Make the data trustworthy enough to build on. Prove to a regulator or an auditor that the controls are real. Then put AI on top of something that won’t fall over.

We’d tell you if a sector were genuinely outside what we can do well. Deep proprietary domain modelling, actuarial pricing engines or clinical decision algorithms, needs your specialists and ours together, and we’d scope it that way rather than pretend otherwise.

What we won’t do

We only build on Google Cloud, with Claude and Wiz alongside it. If you’re committed to staying on AWS or Azure, we’re the wrong firm and we’ll say so on the first call rather than three weeks into a discovery. Depth on one platform is how we can quote a fixed price and a fixed date without padding for unknowns, and that trade-off only works if we hold the line on it.

If your sector isn’t on this page, the fastest way to find out whether we’re useful is to describe the problem rather than the industry.