Fair for riders. Rewarding for pilots. Scalable for us.
Our pricing model is built for efficiency: riders share the cost of a trip the pilot is already making, at a transparent per-km fare with no surge, and we keep a thin 3% platform fee. Recurring commutes mean the same rider travels twice a day, every office day.
Why our pricing is efficient for everyone.
Ride-hailing has to pay a driver for the whole trip, and that's why fares surge. We only split the running cost of a journey that was happening anyway. Riders pay less, pilots recover their costs, and the platform stays lean.
Rates are the ones implemented in our prototype backend. Final launch pricing will be validated with real commuters in our pilot corridor.
Pilots are already making the trip. The fare helps them recover fuel and running costs, so riders pay far less than a dedicated cab.
The fare depends only on distance and vehicle class. The 9 AM commute costs exactly the same as a noon trip.
Bikes, autos, hatchbacks, sedans and vans each have their own base, per-km rate and minimum fare.
The pilot keeps 97% of every fare. There is no fleet to fund and no driver incentives to pay, so we don't need a high take rate.
The rider sees the exact fare on the match card before accepting. No meters, no haggling, no surprises.
Fares and splits are computed in integer paise on the server, and settled instantly over UPI.
Distance × vehicle class. No surge. Ever.
The proposed rate card, as implemented in our prototype. The same trip costs the same at 9 AM as at noon. Fares are computed server-side in paise from the road distance and the pilot's vehicle class.
| Vehicle class | Base | Per km | Min fare | 5 km | 10 km | 15 km | 25 km |
|---|---|---|---|---|---|---|---|
| Bike / Scooter | ₹0 | ₹3 | ₹15 | ₹15 | ₹30 | ₹45 | ₹75 |
| Auto rickshaw | ₹10 | ₹4 | ₹20 | ₹30 | ₹50 | ₹70 | ₹110 |
| Hatchback | ₹15 | ₹5 | ₹30 | ₹40 | ₹65 | ₹90 | ₹140 |
| Sedan / SUV | ₹20 | ₹6 | ₹40 | ₹50 | ₹80 | ₹110 | ₹170 |
| Van | ₹25 | ₹7 | ₹50 | ₹60 | ₹95 | ₹130 | ₹200 |
| Minibus | ₹30 | ₹8 | ₹60 | ₹70 | ₹110 | ₹150 | ₹230 |
Model the business yourself.
We have no revenue yet, so this is a scenario model, not a forecast. Adjust the assumptions to see how gross ride value and platform revenue would scale with daily riders under our pricing model.
Fares use the rate card implemented in our prototype backend (base + per-km, with a minimum fare). Assumes two rides per rider per office day (to work and back). We're pre-launch, so these are illustrative scenarios, not forecasts or actual results.
Commission at launch. A commute platform over time.
The ride commission is how we plan to prove the marketplace. Recurring behaviour, employer relationships and verified savings data could open higher-margin streams on top.
Ride commission
3% of every settled fare, deducted automatically at payment and configurable per market. Already implemented in the prototype.
Employer programs
Company-only pools, commute subsidies and emissions reporting on a per-seat SaaS fee.
Commute passes
Monthly subscriptions for recurring riders: predictable spend for riders, predictable income for pilots.
Embedded services
Ride insurance, fuel and FASTag partnerships, and vehicle services for our pilot base.
Carbon & ESG data
Verified shared-ride savings (fuel, CO₂) from our savings snapshots, packaged for corporate reporting.
Mobility insights
Aggregated, anonymised corridor demand data for planners and real-estate partners.
Low cost and high trust: the quadrant no one serves.
Cheap options aren't trusted or reliable. Trusted options are expensive at peak. Pair My Ride combines peer-to-peer economics with verification, fixed pricing and recurring matches.
vs. ride-hailing: No surge, and a fraction of the fare, because the pilot is making the trip anyway.
vs. informal carpools: Verified pilots, fair algorithmic pricing and UPI settlement.
vs. public transport: Near door-to-door pickup along the pilot's road corridor.
Win one corridor. Then the next one.
Corridor-first launch
Start with dense office corridors (e.g. Koramangala ↔ Electronic City) where routes naturally overlap, and win liquidity street by street.
Seed pilots first
Supply is the constraint. Reverse matching means every new pilot immediately serves riders already waiting.
Tech-park partnerships
Onboard through office campuses, HR teams and employee groups to build instant trust density.
Partner loops
Commute partners turn every good ride into a recurring pair, and every pair into referrals.