About Us

Taru works with you to turn AI from a question into a capability — finding where it creates real value in your business and building the path to get there. He has led data and AI at scale across fintech and banking, from standing up ANZ's first machine learning models to heading data at Squirrel, where AI drives customer experience and operational performance. He knows what it takes to move from idea to production in complex, regulated environments. At the core of it, Taru is a problem solver. The technology is the tool — the work is understanding your business well enough to use it right.

Karen keeps engagements running — connecting the right people, the right process, and the right outcomes so the work actually lands. She brings a background in civil engineering and project management, which means she thinks in systems, timelines, and what it takes to deliver something real. That rigour carries through everything she touches at DoAI. What sets Karen apart is how she works with people. She builds genuine relationships — with clients, with the team, with partners — and that trust is what makes the hard parts of any project manageable.

Toni helps teams take AI from prototype to production — building data-heavy systems that need to run reliably, at scale, every day. She comes from cloud and infrastructure engineering at Xero and BNZ, with deep experience in AWS, CI/CD pipelines, and the tooling that keeps production systems stable — from container orchestration to infrastructure as code. At Do AI, she brings that production mindset to product leadership: making sure what gets built is secure, scalable, and something your team can operate and trust long after launch.

Jamie works with you from problem to product, shaping strategy and design around what your users actually need, and finding the craft in the details. He has designed across enterprises, startups, and government, always close to the technical detail, where business needs and user needs have to meet somewhere real. When AI moves fast, centering yourself on the user and the problem means you build what actually matters.

Andrew builds the client-facing layer of our software and focuses on how people actually interact with what gets built. He finds the most interesting problems are the ones where the right answer isn't just technical, it's about understanding how a person thinks and building something they can trust.