AI decision tools for a ports operator
Research with ship captains that uncovered why vessels waste fuel waiting — and a set of AI use cases designed around the answer.
Client work, shown abstractly. Commercial port operations are sensitive, so there are no real screens, routes, or pricing here — only the research, the insight, and what I designed around it.
A ports and logistics group wanted AI to make its maritime operations smarter: help captains sail at the right speed, forecast where empty containers need to be, coordinate berthing. The question wasn’t “can we build AI” — it was “AI for which decision, made by whom, that’s actually broken today.”
Going to the source
To answer that, I did UX research with people most software teams never talk to: working container-ship captains. When direct access was hard, I recruited through maritime forums. What came back reframed the whole program.
Captains rarely get told a speed — they’re told “maintain ETA” and left to guess. And the reason ports don’t share berth availability isn’t an oversight: keeping that information opaque helps keep terminals full. The fuel waste and idle anchorage time everyone wanted to fix were sitting on top of an incentive problem, not just a data problem. Naming that out loud changed which use cases were worth building.
What I did
- Ran the captain research and synthesized the commercial-team workshops into a current-state map of how voyages and berthing actually work.
- Designed the priority AI use cases — voyage speed intelligence, container repositioning — as exec-ready one-pagers: the problem, the users, what the tool does, the decision it improves, the business value.
- Designed the interface for the container-repositioning tool, including the decision drawer where a planner sees the recommendation and the reasoning behind it.
- Drove the Phase-2 use-case catalog — scoring ideas on desirability, viability, and feasibility, and insisting every one traced back to a real user and a real friction.
Why it matters to me
The strongest thing I brought wasn’t a screen — it was an insight from talking to the right people, and the discipline to let it kill the use cases that wouldn’t have worked. Executives don’t buy dashboards; they buy better decisions. This project is how I learned to design for that.