Every engagement starts with a real need — not a technology demo. The right approach depends on where you are, and what you're trying to solve.
Deploying AI to your teams is a strategy. Deploying it to yourself is a prerequisite. Four to six weeks of hands-on coaching, run personally by Philippe, in person at your workstation — on the work that's already on your desk. You leave with a personal playbook, real deliverables, and the judgment to lead what comes next.
Building on your real workflows, drafting and analysis with the tools, calibrating governance scope, framing buy-versus-build and vendor decisions
Deploying AI tools isn't a transformation. A transformation is redesigning the structure underneath — the standards, the performance systems, the org design, and the roles — so your organization can grow without growing overhead linearly.
SOPs & documentation, performance management, AI Workers deployment, org design, change enablement
A recurring process in your operations is consuming headcount it shouldn't. An AI Worker takes over that role — with defined scope, a reporting line, and measurable KPIs. It runs daily, handles exceptions, and frees your team for higher-value work.
Invoice processing, logistics documentation, performance monitoring, compliance intake
You're facing a massive operational challenge — categorizing 100,000 parts, researching M&A comparables, migrating tens of thousands of patient records. Your team could do it, but it would take months. An AI Solver does it in days.
Mass data categorization, M&A research with comparables, large-scale system migrations, regulatory filing preparation
Most AI deployments underdeliver — not because the technology is wrong, but because the organization wasn't designed to run with it. The standards don't exist. The KPIs aren't tracked. The roles haven't been redesigned.
See the transformation framework →Most AI companies sell technology. Most consultancies sell strategy. We design and deploy AI systems that do real work inside your organization — scoped to a bottleneck, measured on results, and built to be maintained.
Every engagement starts with a specific operational constraint — not a roadmap or an assessment.
Our solutions run daily inside real businesses, handling real data, with real accountability.
We define KPIs upfront and measure against them. If it doesn't move the needle, we haven't delivered.
I led AI and analytics transformation engagements at McKinsey as an Engagement Manager, then built and operated a VC-backed network of tech-enabled medical clinics where I had to implement it — not just recommend it. As a partner at Cylad Consulting, I delivered AI-enabled solutions inside complex industrial organizations. Sterling North is where all of that converges.
No noise. No product updates. Just Philippe's read on where work is heading and what it means for how organizations need to operate.
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