RideMama
Case study

Ride sharing built for the daily campus commute.

RideMama connects students whose colleges sit far outside the city with classmates already driving that way. We designed and built the whole platform: route-aware matching, verified hosts, fixed fares, in-app payments and QR-verified boarding, delivered as an installable app.

Visit live site ↗Start a similar project
Client
RideMama
Industry
Mobility · Ride sharing
Services
Product strategy, UX/UI design, Full-stack development, DevOps
Platforms
Progressive web app, Android (installable)
Live
ridemama.in ↗
roles in one app: rider and host
2
geospatial indexes powering route matching
3
boarding check at pickup
QR
installable on any phone, no store needed
PWA
01

The challenge

Many colleges sit far from the city centres where students live. The daily commute is a long bus ride, a crowded shared auto or an expensive cab, while other students drive the same road with empty seats.

  • Rides that don't fit a timetable

    Buses run on fixed routes and fixed times. Students needed rides that match when their first class starts and where they actually live.

  • Surge pricing on a student budget

    Cab fares spike at exactly the hours students travel. A daily commute needed a price that stays the same every day.

  • Trust between strangers

    Getting into a car with someone you don't know is a big ask. Hosts and vehicles had to be verified, and riders needed to know they were boarding the right car.

  • Routes, not just points

    Ordinary ride apps match two points. A host's car passes dozens of possible pickups along the way, so matching had to understand the whole route.

02

Our approach

We treated RideMama as a trust product first and a maps product second. Every decision aimed to make the first ride feel safe and the hundredth ride feel effortless.

  1. 01

    Match on the route, not the address

    Hosts publish their full driving route. Riders are matched when the route passes near both their pickup and their drop-off, so a host can serve people all along the way.

  2. 02

    Verify people and vehicles up front

    Phone OTP sign-up, vehicle registration with photos and an approval step mean every host is known before they can offer a seat.

  3. 03

    Fixed, fair pricing

    Fares are calculated from distance with no surge, so a student pays the same on a rainy Monday as on a quiet Friday.

  4. 04

    Ship where students already are

    An installable progressive web app skipped app-store friction and let us ship fixes the same day.

03

What we built

One app, two roles. Any verified student can switch between riding and hosting.

Riders

05
  • Search by start, destination and date
  • Route-aware results with the nearest pickup point
  • Seat requests and host confirmation
  • Razorpay checkout with order status
  • QR code to board, ride history and reports

Hosts

05
  • Vehicle registration with photo upload
  • Publish a ride with route, seats and start time
  • Women-only ride option
  • Accept or decline rider requests
  • Start and end rides, scan rider QR at pickup

Platform

05
  • OTP and WhatsApp notifications via Twilio
  • Payment capture, failure handling and history
  • Rate limiting on public endpoints
  • Signed media delivery through CloudFront
  • Reports and moderation flow

Architecture and stack

A lean, container-based stack that a small team could run and ship to daily.

Client
  • Next.js
  • TypeScript
  • Tailwind CSS
  • PWA (next-pwa)
  • Ola Maps SDK
API
  • Node.js
  • Express
  • JWT auth
  • Zod validation
  • Rate limiting
Data
  • MongoDB Atlas
  • 2dsphere geo indexes
  • AWS S3
  • CloudFront signed URLs
Services
  • Razorpay
  • Twilio WhatsApp & SMS
  • Docker
  • GitHub Actions
  • DigitalOcean
04

The details

Matching

Matching riders to routes, not just places

Every hosted ride stores its start, end and full driving route as GeoJSON with 2dsphere indexes in MongoDB. A search first finds routes passing near the rider's start, filters out rides they've already requested, then keeps only routes that also pass near their destination.

  • 01Route stored as a GeoJSON LineString, not just two points
  • 02$near queries against the route with a configurable radius
  • 03Nearest pickup point computed along the host's path
  • 04Fare calculated per rider from their actual segment
Trust & safety

Boarding the right car, every time

At pickup, the host scans a QR code the rider shows in the app. That confirms the right person is in the right car before the ride starts, and it's the event that moves a ride from hosted to in progress.

  • 01Rider QR generated per booking
  • 02In-browser scanner for hosts, no extra app
  • 03Ride states: hosted, in progress, completed
  • 04Women-only rides for riders who want them
Payments

Payments that never leave a seat in limbo

Checkout runs on Razorpay orders with server-side signature verification. Separate capture and failure handlers mean a seat is only confirmed once money has actually moved, and a failed payment releases it cleanly.

  • 01Order created server-side, verified on return
  • 02Capture webhook as the source of truth
  • 03Explicit failed-payment path
  • 04Per-user payment history
05

How it came together

  1. Step 01

    Discovery

    Mapped the commute from the student's side: when classes start, where students live, and where buses and cabs fall short.

  2. Step 02

    Design

    A dark, purple-accented interface built for one-handed use at a bus stop, with the search front and centre.

  3. Step 03

    Build

    Matching, hosting and payments shipped as independent services behind one API, with CI/CD from day one.

  4. Step 04

    Launch & iterate

    Launched at ridemama.in and kept tuning pickup radius, pricing and host onboarding as real rides came in.

06

The outcome

RideMama went live at ridemama.in as a working marketplace. Students book and pay for rides from their phones, and hosts manage their cars, routes and riders from the same app.

  • A live two-sided marketplace

    Riders and hosts on one platform, with verification, payments and boarding checks handled end to end.

  • Predictable commuting

    Fixed fares and route-based matching turned the daily commute into something students can plan around.

  • Ready to grow

    The roadmap covers real-time ride updates over WebSockets, automated RC and DL checks, and a native app.

Services on this project

Want something like this?

Next case studyInnoconflux Publications

A publishing home that looks as credible as the research.

Read the case study→
Atrix Studio

Where ambitious
ideas become reality.

We design, develop, and support digital experiences that turn ambitious ideas into meaningful products.

Let’s Build →