iOS
ShippingThe app you open every morning. Calendar-aware notifications, saved commutes, and a departure board that knows when to ping you. English-first, native-fast.
A personal travel brain for the Netherlands.
Know when to leave. English-first Dutch transit intelligence, built for the internationals who call the Netherlands home.
Launching on iOS soon. Free to use.
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You open an app, type a destination, and figure it out yourself. That's useful. It's not what you actually want. You want to know when to leave — nstop answers that, in English, using your calendar and live network data.
Trains, trams, buses, metros, trolleybuses, and ferries — every Dutch operator, one board.
An illustrative preview of the in-app departure board. The shipping app runs on live Dutch transit data, refreshed every 10 s.
The app you open every morning. Calendar-aware notifications, saved commutes, and a departure board that knows when to ping you. English-first, native-fast.
Free departure search, no sign-in needed. Add an account to sync saved places and commute memory across every browser you use. The surface most people meet nstop on first.
Commute reliability as a service. For staffing agencies, relocation partners, and employers with hybrid-work planning to solve. Activated once the data layer is proven.
The board is the foundation — correct, fast, in English. Everything else builds on top: calendar awareness, reliability scoring, weather-aware routing, and in-app intelligence that learns how you travel. We ship the simplest version of each, then make it smarter.
NDOV Loket (with its successor govi.nu) and the OpenOV community have published real-time Dutch transit data since 2009 — hundreds of gigabytes covering every line, stop, and departure from NS, GVB, RET, HTM, Connexxion, Arriva, Qbuzz, and the rest. KNMI has published the weather data that sits beside it. Nobody has joined the two and asked the question that matters: which lines actually run on time, and when the weather turns, which ones hold up?
We're processing that data now. The reliability model is being validated against real departures. The intelligence that comes out of it powers the consumer app first — and becomes the layer that makes an enterprise product defensible.
Calendar integration, English-first departure board, saved places, basic commute memory. The "Leave at X" notification uses scheduled times and your current location.
"It told me when to leave, and it was right."
The app learns which lines actually run on time and adjusts its recommendations. Bike, OV-fiets, walking, and shared mobility join the route options — Check, Felyx, Greenwheels, Donkey Republic, where available.
"It told me to leave earlier because that line is often late — and suggested a shared scooter to the station."
Weather-delay correlation. Disruption-aware rerouting. In-app AI that already knows how you travel.
"It rerouted me before I knew there was a problem."
Region expansion. Voice. Enterprise packaging. The consumer app proves the tech; the data layer becomes the moat; the enterprise product adds the scalable revenue wrapper.
"It works in London too. And our company uses it for hybrid-work planning."
Connect your calendar and nstop tells you when to leave for your next thing. No searching, no planning — just "leave at 14:23".
Every trip teaches the model a little more. Which lines run on time, which stations transfer smoothly, which routes are worth taking at 17:00 on a Wednesday.
Disruptions, alternatives, platform changes — surfaced before you think to check. Transit intelligence, not just a timetable.