Engineer · technical founder · systems builder
My path runs from native mobile apps and enterprise infrastructure through analytics and data engineering to agentic systems. I design and stand up AI architectures that connect data, models, tools, and workflows into automations that actually run. Today that work converges in Company OS — the low-cost operating layer behind The Unnamed Roads.
Selected work
Data and analytics have followed every stage of my work: first as product signals, then as operational intelligence, then as governed enterprise platforms, and now as the context and feedback loops that make autonomous systems useful.
Agentic infrastructure · 2023–now
Founder, architect, and operator
Designed a self-hosted operating platform where specialized agents, models, data, tools, approvals, and observability work together on real production tasks.
Evidence
What this demonstrates: I can turn emerging AI capabilities into an understandable, governed, and cost-conscious operating system.
Read case studyEnterprise data & ML · 2023–2026
Solo technical lead — architecture, implementation, and operations
Built a governed Databricks platform that connects more than 20 source systems to analytics, machine learning, support intelligence, and reusable data products.
Evidence
What this demonstrates: I can own complex, long-horizon data systems from ingestion and governance to models and decision interfaces.
Read case studyOperational analytics · 2018
Analytics lead — data preparation, dashboard, and decision design
Turned ServiceNow history into SQL-based datasets and a Power BI decision interface for exploring incidents, service levels, recurring patterns, and opportunities for proactive improvement.
Evidence
What this demonstrates: I use analytics to make complex operations understandable and actionable — a principle that still shapes the systems I build today.
Read case studyProduct development · 2014–2016
Founder and mobile product developer
Took a neighborhood-safety product from concept to native Swift and Java apps, a real-time backend, product analytics, and rapid early adoption.
Evidence
What this demonstrates: I have built products from zero, learned from real user behaviour, and made difficult product and business decisions.
Read case studyOne continuous foundation: using data to understand what is happening, analytics to decide what matters, and engineering to turn that understanding into reliable action.
During my software development studies, I was already building dashboards and using data to explain what was happening. Analytics was never a later specialization; it became the foundation I carried into every role that followed.
I founded TUVA and built native Swift and Java apps with real-time reporting, maps, notifications, and product analytics. Reaching 10,000 users in three weeks made user behaviour and feedback part of everyday product decisions.
In enterprise service operations, I began turning infrastructure and support data into repeatable pipelines, Power BI dashboards, and proactive operational insight. Reliability, ownership, and measurable outcomes became part of how I build.
As a consultant and BI developer at XLENT, I scoped and delivered Power BI dashboards across client assignments. Work with GDPR and security added governance, traceability, and responsible data use to the analytics foundation.
At Husqvarna, I used 40,000 daily sessions, 1,470 survey responses, and 30 customer visits to shape a B2B platform across 35 markets. Data connected product strategy to customer reality and operational outcomes.
I began testing ChatGPT close to its public arrival. During 2023 it moved into my daily work for analysis, writing, problem-solving, and code — first through prompts, then through a deliberate library of reusable workflows.
At Husqvarna, I moved from reporting into end-to-end data engineering: reusable ingestion from enterprise systems, 100 Databricks jobs, 200+ notebooks, and 631 governed tables — followed by forecasting, NLP, and applied machine learning.
The first coding loop was simple: ask GPT, copy, paste, test, and refine. It quickly evolved into building full sites and applications conversationally — an early version of what would later be called vibe coding.
Alongside application development, I connected models to Zapier, n8n, APIs, and scheduled processes. Prompts became reusable flows that could collect data, transform it, trigger actions, and improve through feedback.
Models became part of the actual engineering loop: reading the codebase, using context from the computer, implementing, testing, and shipping from the IDE. MCP then connected that loop to enterprise data, documentation, and tools.
I built the operating infrastructure around the models: orchestration, routing, memory, observability, scoped tool access, approvals, and failure handling. That heritage still runs under Company OS — the live map and tool list are the current references.
I am developing TUR Company OS: a control plane with Operator API, Supabase as system of record, durable Inngest workflows, and growth signals from Linear, PostHog, and Raindrop. MCP data pipelines and the Coolify heritage stack remain execution edges — the live map is on Company OS.
For the systems behind this path, see Company OS. For the AI practice steps, see the AI steps log. The applications I use day to day are listed on Tools — Company OS is the current framing for how they connect.
Current chapter · The Unnamed Roads
Product analytics taught me to measure behaviour. Enterprise operations taught me reliability and trust. Data platforms taught me how context moves through an organisation. AI now lets me connect those foundations into an operating layer that coordinates many capabilities across businesses and projects — highly automated, accountable, and extremely inexpensive to run.
This is becoming the technical base of The Unnamed Roads, my venture studio.
The operating loop
Beyond the work
My library is a live, less formal view of what I read, listen to, and follow — across technology, organisations, design, society, and whatever I am curious about next.
Browse my library