01 // about
The person behind the architecture.
Nairobi-based enterprise architect for AI and data with a Mechatronic Engineering foundation - a career spent designing the connective tissue between board-level strategy, enterprise systems, and frontline operations.
Today that means operating as an enterprise architect across data, AI, and automation - and deliberately building toward Chief-level data & AI leadership.
02 // professional story
From machines to operating systems for organizations
Mechatronic Engineering teaches you to think about the whole machine: sensors, signals, control loops, and the inconvenient physics in between. I carried that habit into data and software, where the machines are organizations and the control loops are pipelines, workflows, and decisions.
My work sits at the intersection of engineering execution, strategy, and business operations - the territory of the enterprise architect. I design target architectures and data platforms that hold up in the real world, AI operating models with governance built in, and automation that improves how teams actually work - then I help boards and executives see all of it clearly enough to act.
I build the kind of systems people trust after the launch meeting is over.
03 // how i work
Leadership philosophy
Systems before heroics
If a process depends on someone remembering to do it, it is not a process yet. I design for the team you will have in a year, not the adrenaline you have today.
Legibility is a feature
Platforms, automations, and reports should be explainable in plain language. Automation is only impressive when it makes the work clearer.
Decisions are the product
The goal is not more dashboards. The goal is better decisions - shorter paths from signal to action, with clear owners along the way.
Technology with context
From civic engagement to climate programs, serious technology serves public outcomes when it is built with context, trust, and staying power.
04 // current focus
What I am working on now
- Enterprise data architecture across GCP, BigQuery, and Snowflake - reference models, standards, and platform strategy.
- AI operating models: adoption frameworks, governance, workflow fit, and human-in-the-loop design.
- Intelligent automation programs and team transformation built around n8n, Twilio, and integration-heavy stacks.
- Decision intelligence: KPI architecture and executive reporting that shorten decision cycles.
- Civic and climate engagement technology at scale.
- The Chief-track: deepening board-level fluency in strategy, capital allocation, and organizational design.
A personal note: I work from Nairobi, where "resourceful" is an engineering methodology, not a buzzword. It shows up in how I build.
05 // contact
Start a conversation
If your data, AI, or automation work has outgrown its current shape, I can help make it legible, scalable, and useful.