Two years in, a merger fixed our focus on the Icelandic market and opened a second front: a data engineering and data science department, founded years ahead of when the wider market would ask for it.
By 2015 the single-client start-up of 2013 had momentum, and a merger with Alva sharpened it. The combination did two things at once: it firmed up our commitment to the Icelandic market, and it stood up a dedicated data engineering and data science department alongside the software work.
That was an unusual bet for the time. Most consultancies our size were still treating "data" as a reporting afterthought. We made it a discipline of its own.
From 2015 onward, software engineering and data engineering grew as twin disciplines rather than one serving the other. A client could come to us for a product and leave with a data platform, or come for analytics and find engineers who could ship the thing they were measuring.
Founding a data practice this early also bought us time. By the time the market started talking about lakehouses, MLOps and AI, we'd already been doing the foundational work for years.
The department born in 2015 is now half of what Moberg is. It's the line that runs through machine learning in production in 2017, the platform era in 2020, and the Microsoft and Databricks data & AI designations that came later. The merger didn't just add headcount — it set the company's second pillar in place.
The data practice grows up — models live across sales, marketing and risk.
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