How TraceMark Flow Is Changing the Way Cities See Traffic
Traffic congestion is a problem every city faces, but few can quantify it in real time. It's a problem NGIS has been working to solve for over a decade, and one that recently earned the team recognition from Google Maps. On a recent episode of Location Matters, NGIS' Director of Transport and Smart Cities, Oliver Looker, sat down to talk about that journey and TraceMarkTM Flow, the innovative transport management tool at its centre.
A decade in the making
TraceMark Flow is a next-gen traffic management tool powered by Google's Road Management Insights. On its own, data is just data. TraceMark Flow's job is to turn it into intelligence that transport agencies and service providers can actually act on.
The product's roots go back to 2015, when NGIS began building tools around Google's data for Transport for NSW. A decade on, that work has been recognised with a Google Maps Platform 2025 award for the engineering and product work behind TraceMark Flow, a milestone Oliver Looker credits to the team of software engineers and product managers who have refined the platform over the years.
Complementing, not replacing, existing infrastructure
Cities already invest heavily in traffic infrastructure, SCATS-controlled traffic lights, inductor loops at intersections, CCTV networks. TraceMark Flow isn't designed to replace any of that. Instead, it layers Google Maps data on top, filling gaps in coverage and giving agencies a more complete, timely picture of what's actually happening on the network, all anonymised and aggregated, drawn from the everyday use of Google Maps and Waze rather than purpose-built sensors.
That combination matters most when it comes to reliability. Early conversations with transport agencies made it clear that predictability how consistent the trip is from the airport to the city, or along key freight corridors is often what agencies and commuters care about most.
Where AI comes in
TraceMark Flow's predictive capability comes down to data consolidation: the more data sources brought together, the more accurate the predictions. That includes overlaying weather events, seasonal patterns and major events to anticipate how conditions might shift, an early step toward a digital twin of a city's transport network. Generative AI features also let users query the platform in plain language, surfacing the metrics and insights that matter most without needing to interpret dashboards manually.
The platform also supports network resilience planning, combining weather, terrain and infrastructure data to help agencies understand risk to road networks under longer-term scenarios, including extreme weather events like cyclones and flooding.
Proof in practice
One example is CERTH, a research centre in Thessaloniki, Greece, working through the disruption of a major flyover project. By mapping key road corridors and layering TraceMark Flow, the team quantified a roughly 40% impact on travel time, data the agency then used to identify alternative corridors and monitor the effects of mitigation efforts over time.
In New Zealand, TraceMark Flow has helped transport teams identify congestion causes across both islands, distinguishing, for instance, between incidents, traffic light phasing issues, and genuine capacity constraints, so the right team can act on the right problem.
Getting started
Implementation is less about the technology, which the team has "down to a fine art", and more about the conversation: understanding an agency's priority corridors, how much of the network they want to monitor, and what that means for scope and pricing. From there, configuration is fast, with agencies typically up and running within a few weeks, supported by workshops and training along the way.
This post is based on an interview with Oliver Looker, Director of Transport and Smart Cities at NGIS, on the Location Matters podcast: Listen to the episode now.