The founder of UnVale
From Assembly Lines
to Data Pipelines.
UnVale started from a simple idea: the engineering that finds waste on a production line can find it in a company’s data too.
Manufacturing Engineering
I studied Mechanical and Manufacturing Engineering at the University of Warwick, then started my career on the factory floor at CNH Industrial. As a Manufacturing Engineer on tractor production, my job was to find the bottlenecks, cut the waste and keep complex assembly lines running smoothly.
Enterprise Data Systems
Over the next five years I took the same skills into data, working with large organisations including HSBC, Charles Stanley and Daily Mail Group Events. The problem was the same: complex, messy environments where something valuable (data, not parts) was being lost along the way.
Getting to the Truth
For these organisations I built and integrated data systems. The goal was never just to move data around. It was to give management numbers they could rely on: pulling in all the data available, checking it was right, and making the real state of the business easy to understand.
Across my career before UnVale, I:
- Built data quality for multi-billion-dollar businesses.
- Introduced AI monitoring systems that watch fields and tables, learn what normal looks like, and flag when something doesn’t look right.
- Built deduplication tools that ran across 22 million contacts, matching on names, addresses, emails, job titles and functions.
As founder of UnVale, I lead our team in bringing that same production-line discipline to founders of commerce businesses: find where things are being lost in your data, fix it, and put it to work.
Let's audit your data supply chain.
Duplicate customers, reports you can’t trust, demand you can’t predict. The cause is usually somewhere in the data pipeline, and that’s where we start.
Start with a 7-day diagnostic