How Cape Town commutes — in real time.
Every question a commuter asks is a signal. PRASA ai turns millions of WhatsApp messages into a live view of the network the way passengers actually experience it — demand, sentiment, and the exact places riders feel left in the dark.
Figures below are illustrative, sized to a Cape Town Metrorail-scale service. Connect live analytics to make them real.
This month at a glance
Where people want to go
Origin–destination demand straight from “how do I get from X to Y” — the data operators normally pay for in one-off smart-card studies.
Most-requested routes queries this week
Demand by time of day relative message volume
Two sharp peaks: 07:00 AM and 17:00 PM. Midday and overnight are quiet.
How riders feel — and where they’re blind
An always-on satisfaction signal from message sentiment, plus the stations and times generating the most “is my train even coming?” — the clearest ROI for better communication.
Sentiment by line
Top passenger concerns
Information-gap hotspots
Where riders feel left in the dark
- 1 BellvilleAM peak · 06:30–08:00
- 2 Cape TownPM peak · 16:30–18:00
- 3 KhayelitshaAM peak · 06:00–07:30
- 4 MutualPM peak · 17:00–18:30
- 5 RetreatAM peak · 06:30–07:30
The recovery, in context
Passenger-side metrics aligned with PRASA’s own goals — so the conversation is about the same numbers.
Trains on time last 12 months · target 90%
The same lens, beyond the trains
This dashboard is the train. System Sol is extending the same passenger-sourced intelligence across how South Africa moves and speaks.
GABS ai In build
Golden Arrow buses, on WhatsApp
YourGov Coming soon
A nation’s voice, on WhatsApp
Fleet ai Coming soon
Fleets, managed from chat
This is intelligence a R20-billion recovery needs.
For the price of a chatbot, PRASA and the City get a continuous, city-wide, passenger-sourced view of demand, sentiment and information gaps. Let’s talk about making it official — or about reaching this audience.