Cameron Batt
Cameron is a machine learning researcher and full-stack developer who founded Skubl after spending years watching the same problem play out across industries: organisations spending billions acquiring users, then sending them to brittle, reactive infrastructure with no predictive intelligence.
His career spans both sides of the gap — from running performance marketing agencies managing multi-million pound budgets, to deep ML research in causal inference and computer vision. That dual perspective drives Skubl's core thesis: the observability stack should predict, not just report.
Skubl is built on proprietary technology, not LLM wrappers. Cameron's research in causal inference models and real-time behavioural simulation at scale forms the engineering moat — purpose-built systems that sit inside network traffic, analyse millions of sessions in real time, and take autonomous action to prevent failures.
Building the Self-Healing Internet
"We are moving toward a world where technology disappears. When you use an app or visit a site, it should just work. It should anticipate your intent and adapt to your needs instantly. Skubl is the engine that makes that possible."
Cameron's vision for Skubl extends beyond observability tooling. He's building the logic layer for the next generation of the internet — where digital infrastructure has an immune system that detects and repairs friction before users encounter it.
The philosophy is simple: humans become the architects, and agents become the workforce. When Skubl's predictive engine handles the observation and remediation of infrastructure, engineering teams are freed to focus on strategy and innovation rather than firefighting.
From the Ad-Tech Gap to Predictive Intelligence
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Interested in working with Cameron or learning more about Skubl's predictive intelligence platform?