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RideNow – Urban Rental App for Scooters and E-Bikes

The client needed a rental app that allows users to easily book, unlock, and pay for scooters, e-bikes, and e-motos. In just 10 months, our team delivered a fully functional, scalable urban rental app and admin system. It helps optimize logistics, reduce maintenance costs, and scale their services across different cities.

client

RideNow

industry

MaaS

platform

Mobile

10 months

Duration

6 employees

Team

Request

Our task was to build an urban mobility platform that would facilitate short-distance travel for city residents. It had to combine scooter, e-bike, and e-moto rentals into a single application. The client also requested a back-end system for operators to manage the vehicle fleet and track their performance.

Challenge

The main challenge was to develop a fully connected system with real-time monitoring and analytics. The app required KYC verification, payment integration, and IoT connectivity to unlock vehicles and track trips. We also had to implement geofenced zones, scalability for multiple cities, and an AI module that checks for damage, notifies support, and helps operators manage and optimize fleet distribution.

Our solution

The Yojji team built a user app and operator dashboard. Users can quickly book, verify identity, and unlock vehicles via IoT integration and secure Stripe payments. The operating system displays fleet activity, battery levels, and analytics. An AI model detects vehicle damage from photos and alerts support. Our scalable architecture also allows easy deployment across multiple cities.

Core Features

Seamless IoT Integration

We integrated IoT technology, so users can quickly find and connect the app directly to each vehicle to unlock, start, view designated city zones, and end rides. The system also allows riders to open the helmet compartment remotely and automatically begins ride-time tracking once the session starts.

KYC & Payment System

Compliance and user safety were our priorities. We integrated KYC verification for quick and document checks directly within the app. Then, users can pay instantly and securely with Stripe, and operators have transparent control over billing and refunds.

AI Damage Detection

Our dev team integrated the AI model. How does it work? Users upload a photo of the vehicle at the end of the ride. The AI system automatically detects scratches, broken mirrors, or missing parts and immediately alerts the support team. This solution reduces inspection time, prevents disputes, and maintains vehicle quality across the entire fleet.

Fleet Management & Analytics System

Our client also got an operator dashboard that gives full visibility into fleet activity, usage, and performance. The system tracks battery charge levels, location data, and trip frequency in real time to plan maintenance and optimize logistics. Built-in analytics tools identify the most popular areas and vehicle types so that they are always available in high-demand areas.

Results

  • Our team delivered the platform in 10 months. It includes a user app, an operator dashboard, IoT integration, payments, KYC, and AI-based damage detection.
  • Up to 45% reduction in manual fleet inspections after introducing AI damage detection from rider photos.
  • 27% faster vehicle turnaround due to real-time battery monitoring, location tracking, and automated maintenance alerts.
  • Lower maintenance costs per vehicle by identifying damage immediately after rides instead of during scheduled checks.

Technologies we used

react
React Native
postgres
Postgres
js
JS
nestjs
Nestjs

Project team

Inna R
Inna
Head of Design department
Igor
Full Stack Developer
Boris Feoktistov
Boris
Software Developer
Yevhen
QA Engineer

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