We turn traffic data into signal plans, networks and decisions that are tested and proven before they reach a single street.
> the problem
> Built in-house
Artificial intelligence,
built only for traffic.
Traffic is so complex that only artificial intelligence can solve it. So we created our own.
Its one goal is to understand traffic, street by street, then town, city and country, and to learn to control it. No off-the-shelf solutions. No generic agents.
> how we work
// 001
Measure
A clear picture of how people actually move through your streets, hour by hour.
// 002
AI modelling and advanced simulation
A digital copy of your streets, where every idea is tested before it reaches the road.
// 003
Design
AI trained on traffic designs the plan, with the evidence for why it wins.
// 004
Deliver & monitor
Support during rollout, and the result measured on the real street afterwards.
> case study · kaunas
4.4×
Shorter side-street wait
1.8×
Side-street cars served
1.5×
Flow for worst-off 10%
+51%
Average vehicle speed
City plan
Our plan
> about us
Traffic is a
science problem.
Traffic engineers and data scientists. We work alongside the engineers who run the signals today. The goal is to make their work better, not to replace it.
Story
Lights that don’t seem to care
We began applying machine learning and simulation to traffic control, first at scale, then street by street.
Mission
Every street at its best
Make every street work as well as it possibly can, from the busiest junction to the quietest side street.
Vision
Plans that stay current
Cities where every signal runs the best plan the data can find, kept up to date instead of revisited once a decade.
> faq
Questions cities ask us first
Municipalities and city traffic departments, road authorities, engineering consultancies, planners and developers, public transport operators and event venues.
No. Clearance times, conflict tables and pedestrian calls are hard limits in every search. A plan that breaks one is never saved.
Both, and we always say which. Plans are proven on a digital twin validated against the real street, then measured again after rollout.
With an audit: measured data, a validated model, a diagnosis and a recommended fix, within a scope agreed up front. Larger studies and live pilots build on it.
Yes. Before/after evaluation works for any intervention, including ones we didn’t design.
> Start with an audit
Tell us where.
We’ll bring the intelligence.
or write to hello@oxusmorus.com, or call +370 (620) 33 008
or read how we tested our system in action: Kaunas case study