Fares, timetables and charging points, on one map.
Mobility decisions depend on what a journey costs and how easy it is to make, by route and time of day. We capture ride-hailing fare estimates, public transport timetables and fares, micromobility pricing and EV charging points, and structure them for planners, operators and investors.
What makes this industry hard to track.
Fares vary by time and demand
Ride-hailing estimates change with demand, so a route needs repeated captures across the day and week to be understood.
Timetables in many formats
Operators publish timetables as open feeds, web pages or PDFs, and revise them seasonally.
Charging point data quality
Charging locations, connector types, power ratings and tariffs are listed inconsistently and change as networks expand.
Route definitions
Comparisons only work if routes are defined consistently, by origin and destination points rather than loose place names.
Eight data points our clients rely on.
Ride-hailing fare estimates
Quoted fare range by product tier, route and time of capture.
Surge indicators
Whether dynamic pricing is applied at the time of capture.
Estimated pickup time
Quoted wait time for each product tier.
Public transport timetables
Routes, stops, frequencies and first and last services.
Public transport fares
Single, return and pass prices by zone or distance.
Micromobility pricing
Unlock fees and per-minute rates for shared scooters and bikes.
EV charging points
Location, operator type, connectors, power rating and number of bays.
Charging tariffs
Published price per kWh or per minute and any session fees.
An illustrative extract.
| Captured at | Source | City | Route | Distance (km) | Fare estimate | Currency | Surge |
|---|---|---|---|---|---|---|---|
| 2026-09-04 08:15 | Ride-hailing App A | Riyadh | King Khalid Airport to Olaya | 35 | 95-110 | SAR | No |
| 2026-09-04 08:15 | Ride-hailing App B | Jakarta | Soekarno-Hatta Airport to Sudirman | 32 | 185000-215000 | IDR | Yes |
| 2026-09-04 08:20 | Ride-hailing App C | Bogotá | El Dorado Airport to Chapinero | 15 | 32000-38000 | COP | No |
| 2026-09-04 08:20 | Ride-hailing App D | San Francisco | SFO to Union Square | 22 | 48-56 | USD | Yes |
| 2026-09-04 08:25 | Ride-hailing App E | Paris | CDG to Opéra | 28 | 52-60 | EUR | No |
Illustrative rows. Sources, markets and fields are agreed with you during scoping.
How teams put it to work.
Fare benchmarking by route
Repeated fare estimates on a fixed set of routes and times, showing price levels and surge patterns across operators.
Network and service mapping
Timetables and fares from public transport operators, joined to stops and routes for accessibility and catchment analysis.
EV charging coverage
A current inventory of public charging points, power levels and tariffs by city, showing gaps for network planning.
Relevant solutions
Related industries
How do you capture ride-hailing fare estimates?
We request fare estimates for fixed origin and destination points at scheduled times, as a rider would before booking. No rides are booked, and each estimate is stored with its route, time and product tier.
Can you combine timetables from different operators?
Yes. We take open timetable feeds where they exist and extract from web pages or PDFs where they do not, then standardise everything to a single stop and route structure.
How current is EV charging point data?
We refresh charging point inventories on a schedule agreed with you, often weekly, and record additions, removals and tariff changes between runs.
Is any personal location data involved?
No. We capture fares, schedules and infrastructure, not the movements of individuals. Routes are defined by fixed points you choose.