An AI and data engineer who started in sales.

How I got here

I started on the phones. A sales floor at a bank in Cardiff, then a recruitment desk, then selling holiday properties abroad and sponsorship at a B2B technology events business. Four years of targets, call sheets and Monday pipeline reviews, and a growing suspicion that the people who built the systems we sold from had never sat where I was sitting.

At 25 I went back to university. Computer Science at Cardiff Met, a first-class degree and Computing Student of the Year at graduation, with a semester in Eindhoven on applied data science in the middle of it. It felt late at the time. It was the best decision I have made.

The decade after that was data. A year at GE on business intelligence while I was still studying. BT's graduate programme as a big data engineer. A two-year Knowledge Transfer Partnership with Innovate UK, researching and building new data models into a marketing attribution platform. Then streaming pipelines at confused.com, in Databricks and PySpark, feeding the marketing team numbers they could act on the same day.

Then Cubed, where the two halves met. Solutions engineer on a marketing analytics SaaS, sitting between the engineering team and the sales manager on enterprise deals. Scoping the requirement, designing the integration, running the demo, closing the loop. It was the first job where writing the pipeline and holding the commercial conversation turned out to be the same skill.

I was made redundant in November 2024. APEX AI started the following month.

What that gives you

What that means for your team.

I know what it is for. I have carried a number. I know what a rep will actually open on a Monday morning, how much of a sales week goes on research and admin instead of conversations, and what a sales manager will trust in a pipeline review. So the question I start from is the one you care about: how does this team get more pipeline without hiring more people?

And I can build the answer properly. Research agents, signal feeds, follow-up that runs itself, and the CRM and data underneath all of it. Built like software rather than configured in a no-code tool and abandoned, with a defined answer for what happens when something fails at three in the morning.

How I work

Founder-led, and deliberately so. I scope and build the work myself, and bring in specialist help when a project needs it. I work from Cardiff with clients across the UK, Europe and the US, and almost all of it happens without anyone being in the same room.

Every engagement starts with the Pipeline Audit rather than a pitch, because scoping a build off a guess is how projects go wrong. Fixed scope, fixed fee, with the limits written down. And I will tell you when something is not worth building, or when I am the wrong person for it.

Outside of work there is a son born this summer, and a Fantasy Premier League team that gets more data engineering than it deserves.