The future of city infrastructure is now. At vialytics, we’re helping municipalities turn data from the field into smarter decisions, and faster. In our recent joint webinar with our partner Encord, we pulled back the curtain on how our AI-driven platform powers decisions in real time for road maintenance and infrastructure planning.
Seven years ago, our team built our first pavement-condition algorithm running on a laptop with manually labeled data. Fast forward to today: thanks to cloud computing and state-of-the-art annotation tools, we’re processing millions of images across jurisdictions — automatically. Friedrich Münke, our Director of Data Science, walked through how the Encord platform helped streamline everything from annotation to model training and quality control.
Here’s how it works in the field: paired with a standard smartphone, our mobile app captures an image every ~13 feet (≈4 meters) while surveying pavement conditions. Our AI then detects pavement distress, traffic signs or drainage issues and maps those findings digitally.
Why it matters: cities and public-works agencies get a real-time, objective inventory of road conditions — helping them decide where to allocate scarce resources, even when staffing and budgets are tight. As Friedrich puts it: “We’re creating transparency and making sure administrations invest where it matters most.”
One major topic from the webinar: data is never perfect. Our image feed comes from real city-fleet vehicles capturing data in sun, rain, dusk, and low light. “We ask users to survey in daylight, but our AI has to deal with everything,” said Friedrich.
That means: reflections, wet roads, blurry images, each one is a challenge. His guiding mantra: “Data quality matters more than model complexity.” To support that, our team uses strict labeling rules, multi-stage reviews and ongoing quality audits. And because our system is already live across Germany, France, and the U.S., our models handle varying traffic signs and road types seamlessly.
“If performance drops in a region, we feed in targeted new examples until it’s back up to standard,” said Friedrich. That’s how we ensure our platform remains consistently reliable under real-world conditions.”
Looking ahead, the rise of multimodal AI opens exciting possibilities. Imagine querying your city’s network: “Show me all the traffic signals in my district” or having a smart assistant guide maintenance crews based on current data. Friedrich predicts that within five years, infrastructure management, from detection and work-order generation to documentation of repairs, will become significantly more automated and interconnected.
Our webinar demonstrated how vialytics is making it easier for cities to manage roads intelligently and bring smart-city ambitions into practice. With a powerful AI stack, deep operational insight and a focus on real-world use, we’re delivering more than software — we’re enabling better outcomes for communities.