Twenty-five years ago, providing traffic information felt like alchemy. In the late 1990s and early 2000s, data was sparse. We relied on a patchwork of sources and a lot of phone work, calls to CCTV control rooms and early “jam lines” from drivers on the roads.
Our challenge was turning trickles of raw information into useful traffic news. I remember teams manually gathered reports of accidents and congestion, scrambling to verify and broadcast them in time to matter.
The goal was simple but profound: turn scattered data points into actionable knowledge for drivers. To do that, we built some of our earliest software systems to log, structure, and validate every report. Those formative years taught us a lasting lesson: even small amounts of data can be powerful when refined with the right technology.
One of my first major projects focused on delivering traffic news more efficiently across the UK. At the time, most updates came from radio presenters reading bulletins. We wanted to automate that process and in 2001, it led to a breakthrough: the UK’s first commercial RDS-TMC traffic service, launched nationally in partnership with Toyota. For the first time, drivers’ satnavs could receive live traffic alerts via FM radio and automatically reroute around congestion. We had effectively digitized the traffic bulletin, laying the foundation for many of today’s navigation services.
From Radio to Data Feeds: Serving Public and Enterprise
As our data capabilities grew, so did our audience. What began as raw material for radio reports evolved into structured data feeds for a variety of clients. We started supplying structured traffic data to public sector agencies and enterprise customers as early as 2003. This meant government traffic centers, mapping companies, and media outlets could ingest our information directly into their systems.
Our company, then known as Trafficlink in the UK, provided real-time traffic info to the BBC’s travel websites and local radio, as well as to commercial broadcasters and online services. We also delivered data to emerging navigation software and automotive infotainment systems through our UK partner ITIS. This shift, from broadcasting reports to sharing data via APIs and feeds, was another form of transforming data into knowledge. Instead of just telling drivers about congestion, we began powering the tools they used to find optimal routes. It was exciting to see our information being used in ways beyond radio, from on-screen driver alerts to analysis for urban planning.
In effect, we were building a traffic data ecosystem: one that served consumers via media and drivers via satnav, while also guiding professionals in transportation agencies and businesses. This period taught me the importance of data quality and consistency. When information feeds public systems or enterprise applications, accuracy and trust are essential. We invested in validation and filtering to ensure our data delivered high-quality, actionable insight for everyone; from city traffic engineers to everyday commuters.
Turning Point: Going Global with Real-Time Incidents
The true turning point in my journey came in the 2010s, when our traffic data efforts went global. In 2011, INRIX, a rising company in traffic intelligence based in the U.S., acquired our UK business. Almost overnight, what had been a largely UK-focused operation became part of a worldwide real-time traffic incident platform, serving drivers and partners across Europe, North America, and beyond. Our reach expanded rapidly to dozens of countries and hundreds of millions of drivers. For me, it was both exhilarating and daunting — it’s not often you see a project grow from one region to 30 countries at once!
Going global meant far more than just serving more customers; it fundamentally changed how we operated. We now had to fuse data sources, systems, and teams from around the world into a single cohesive platform. Our incident data pipeline started ingesting information from across continents – everything from European motorway control centers to U.S. state DOT alerts to emerging sources in Europe. We had to adapt to different road networks, languages, and reporting standards, unifying them under one consistent INRIX platform.
One of the biggest challenges was ensuring consistency and reliability at scale. An incident on the M25 in England needed to be detected, located, and distributed with the same speed and accuracy as one on I-95 in the United States. We upgraded our location-referencing systems and built more scalable architectures capable of handling dramatic increases in data volume and user demand.
Crucially, this global expansion also brought new technical capabilities. Through the integration of ITIS, INRIX added around 20 million connected devices worth of data from ITIS’s network to its traffic platform, significantly strengthening its cellular probe data and connected vehicle expertise. T This marked a major leap forward in crowd-sourced traffic intelligence: more probes meant faster detection of congestion and incidents, broader coverage, and greater accuracy. At the same time, we combined the UK team’s experience in RDS-TMC and digital broadcast traffic with INRIX’s strengths in GPS probe analytics, creating a richer and more resilient data ecosystem.
I often reflect on that moment; it felt like the culmination of years of groundwork. The systems and methodologies we developed in the UK proved robust enough to scale internationally. And for our customers (automakers, governments, mobile app providers), it meant access to a single, global traffic incident feed rather than fragmented regional solutions. It was then that I clearly saw the unifying thread of our work: no matter the country or data source, the mission remained turning raw traffic data into useful, actionable insight for people on the road.
Data Deluge: Harnessing the GPS and Smartphone Revolution
By the mid-2010s, the data trickle of the 1990s had turned into a firehose. The proliferation of smartphones, connected cars, and IoT sensors created a superabundance of location data. Instead of struggling to find information, our challenge became synthesizing meaning from massive volumes of it. Every day, INRIX systems were ingesting billions of anonymous GPS data points from vehicles and devices worldwide. Individually, each ping revealed a vehicle’s speed and location; together, they painted a near-real-time picture of traffic flow across virtually every major road.
The mission remained the same; turn this data into useful knowledge, but the methods had to evolve. INRIX invested heavily in machine learning and AI algorithms to automatically detect incidents and congestion patterns from live data streams. We developed predictive analytics to forecast traffic conditions (so drivers and city planners could act ahead of time), and historical analytics to find trends (like the average congestion for every hour of the week on a given road).
In 2019, INRIX introduced INRIX AI Traffic, marking a new generation of traffic intelligence that leverages artificial intelligence for unprecedented precision in traffic speed and incident data. The result of this innovation was more precise and actionable insight: navigation apps that re-route you instantly, city traffic systems that adjust signal timing based on real-time flows, and logistics companies that can schedule deliveries smarter.
Amid this data deluge, we also faced a growing responsibility: protecting privacy. As data volumes increased, so did the importance of handling that data ethically and anonymously. We embedded privacy-by-design principles into our platform, stripping personal identifiers and relying only on aggregated, anonymized location data. Measures such as hashing device IDs, obscuring trip endpoints, and never storing information that could identify individual drivers became essential, particularly as regulations like GDPR emerged and public concern around data use grew.
I’m proud that throughout this data revolution, we kept privacy at the core of our work. We demonstrated that it’s possible to harness billions of data points to improve mobility without compromising personal privacy. This balance of innovation and responsibility is something I’ve seen evolve and solidify over my 25-year journey.
The AI Era: Full Circle to Automated Traffic Reporting
As we entered the 2020s, the convergence of rich data, decades of expertise, and new AI techniques unlocked something almost magical: we came full circle to automated, AI-generated traffic reports—the very kind we once delivered manually on the radio. This year, INRIX launched the AI Traffic Reporter, a platform that can produce real-time traffic news updates entirely with artificial intelligence.
It feels like science fiction brought to life. Using more than two decades of proprietary traffic data combined with generative AI, the system automatically scripts and voices traffic bulletins for any location, at any time. With synthetic voices that sound like human broadcasters, it can deliver instant updates on radio or television the moment conditions change. Essentially, we have taught an AI to do what traffic reporters have done for years – but faster and around the clock.
For me, having started in an era when we literally phoned in reports, it’s extraordinary to see an AI now handle the entire process, from detecting an incident to broadcasting an update, in seconds. It’s a powerful reminder of how far technology has come. More importantly, it means drivers and transportation agencies receive information with almost no delay, helping reduce secondary accidents and congestion by alerting people sooner.
What I love about this development is how it ties our journey together. It’s the unifying thread in action: using cutting-edge technology to turn data into usable knowledge. In 1998, that meant a person with a radio and a telephone; in 2025, it means an AI with billions of data points. The format has come full circle to audio reports, but now entirely automated.
Notably, this AI revolution arrives at a time when data privacy is more important than ever. The AI Traffic Reporter relies solely on robustly anonymized and aggregated data, extracting insights without exposing individual information. It’s a win-win: better, faster information for the public and partners, delivered instantly and responsibly. Standing at this point, I feel both the excitement of innovation and the responsibility of continuing the mission that began for me 25 years ago.
Innovation, Data, and the Road Ahead
Reflecting on this 25-year journey, I see a remarkable evolution in both our industry and INRIX’s story. We moved from sparse data to streaming data, from manual reports to machine learning, and from local trials to global platforms—always with the aim of making mobility smarter and safer. The unifying thread throughout has been innovation: transforming raw data into actionable insight. From pioneering delivery methods like RDS-TMC in 2001, to scaling a global traffic network in 2011, to deploying AI-driven insights in 2025, each chapter built on the last. Together, they have kept us at the forefront of what’s possible in traffic intelligence.
On a personal note, it has been deeply rewarding to witness and contribute to this evolution. Some of the most fulfilling moments of my career came from taking risks—launching new services, embracing emerging technologies, and seeing them make a real difference for millions of travelers. Along the way, I’ve learned that while technology evolves rapidly, certain principles remain constant. Data quality, timeliness, and user trust mattered in the era of radio bulletins and matter just as much in the age of artificial intelligence.
Looking ahead, I see even deeper integration of AI, from predictive models that anticipate traffic before problems arise to tools that help cities design smarter transportation systems more intuitively. Through all of this, INRIX remains committed to protecting privacy and honoring the trust placed in us by drivers and partners.
From my vantage point at INRIX, the past 25 years have transformed transportation data beyond what I could have imagined as a young engineer in the 90s. And yet, I feel we’re just getting started. With connected cars, smart cities, and AI copilots, the road forward promises to be even more transformative. Thank you for being part of it, whether you’re a colleague, a customer, or a driver who’s benefited from a timely traffic alert, you’ve been part of this story. Here’s to the journey so far, and the road still to come.