A selection of the kind of work we do across data, AI and integration.
Challenge: Five disconnected systems meant a week of manual spreadsheet work each month — and numbers no one fully trusted.
Approach: Consolidated everything into a single modelled warehouse with automated, self-serve dashboards.
Challenge: Thousands of inbound documents a week were being sorted and keyed in by hand, creating delays and errors.
Approach: An AI pipeline that reads, classifies and routes documents automatically, escalating only the exceptions.
Challenge: Patient operations data lived in tools that didn't talk to each other, so reporting was always out of date.
Approach: Built real-time integrations and a unified data layer feeding live operational dashboards.
Challenge: Sales, stock and e-commerce data sat in separate silos, making forecasting guesswork.
Approach: Integrated the sources, modelled the data and delivered forecasting dashboards the team could act on weekly.
If any of these sound familiar, let's talk about what a similar project could look like for you.
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