On the evidence, before the figures
Everything on this page except the CTO Craft 100 listing is my own record of the work. The code, the infrastructure and the histories are the company's and stayed there when I left, so nothing below is a measurement and I will not dress it as one. What I can tell you is the size of what I ran: on the order of 120 repositories, around 70 containerised services, 50-plus CI pipelines, 30-plus Helm charts and several hundred Terraform files across AWS and GCP. Those figures are approximate, and they come from having owned that estate for six years rather than from a count. They establish the scale. They do not establish the outcomes. References can, and I can put you in touch with them.
The problem
A computer-vision retail-analytics SaaS starting from nothing, in a field I had not worked in. Physical retail generates enormous quantities of video and sensor data, and almost none of it reaches a decision-maker in a form they can act on.
The constraints
- Entered with no prior computer-vision experience.
- A 15-person company, so I owned the full technical organisation while remaining an individual contributor.
- Enterprise buyers with security reviews, data-residency and audit requirements.
- Venture funding, which sets the pace and puts technical due diligence in front of you at intervals.
What I built and led
- Led the technical side of a EUR 3M+ seed round (Act Venture Capital, Sure Valley Ventures, Furthr VC, Enterprise Ireland): due diligence, live demos and investor governance. Supported the company to EUR 1M+ ARR at 60%+ margins.
- Built the data platform and multi-cloud infrastructure: Cisco Meraki cameras and sensors across 1,000+ retail locations into an AWS lakehouse feeding dozens of computer-vision use cases, among them vehicle detection, PPE detection, and queue abandonment. AWS and GCP with 25+ Terraform modules behind the 25+ microservices of the analytics platform, processing millions of video-analytics events daily. Cut infrastructure cost 80 to 90 percent with 99.9%+ uptime over five years.
- Deployed Kubernetes with observability (ELK, Prometheus, Grafana) and ML serving via NVIDIA Triton, taking production deployments to five minutes, and ran on-premises edge inference with Cisco's Emerging Tech and Innovation division.
- Zero security incidents in six years on a zero-trust architecture. SOC 2 Type 2 preparation led, with the audit in progress at my departure. GDPR-scope point-of-sale integration across 20+ countries.
- Led 10+ engineers across six countries at 90%+ retention, hired 12, cut sprint lead time from 19 days to 5, and led technical due diligence for a prospective exit.
What was handed over
A technical organisation that ran without me, an infrastructure estate defined in code, and the SOC 2 programme in flight with the audit underway. Named in the CTO Craft 100, 2024/2025 , which is the only item on this page with an external published source.