TABLE OF CONTENT

About the Client

Wapanda is a New Jersey-based taxi aggregator offering a unique ride-bidding system that benefits both riders and drivers. Unlike traditional taxi services, Wapanda allows riders to negotiate fares while enabling drivers to counter-bid, ensuring mutually beneficial pricing. Currently operating in Jersey City, Wapanda has ambitious plans to expand across the U.S., providing a competitive, fair, and transparent ride-hailing experience.

Business Situation

Basic Project Blueprint: Needed a structured development plan from ideation to execution.
Scalability Concerns: Required a robust cloud infrastructure to support future expansion.
User Experience Issues: Required an intuitive design for both drivers and riders.
Ride Fare Calculation: Needed custom algorithms for bid-based pricing.
Payment Integration: Ensuring secure transactions directly between riders and drivers.
Operational Visibility: Required an admin panel for monitoring rides, drivers, and payments.

The Solution

Unthinkable provided a full-cycle development approach, starting with business analysis, project planning, and implementation. Through a Discover & Frame workshop, the team refined Wapanda’s concept, created a strategic roadmap, and established an agile development process. A robust cloud-based system was built using AWS, ensuring scalability and cost efficiency.

Ride-Bidding System: Riders could bid on fares while drivers counter-bid in real-time.
Price Comparison Engine: Allowed users to compare fares with Uber, Lyft, and taxis.
Secure Payment Processing: Stripe integration ensured seamless transactions.
User-Friendly Interface: Intuitive design for effortless ride booking and management.
Admin Dashboard: Enabled real-time monitoring of drivers, rides, and earnings.
Cloud-Based Scalability: AWS-powered infrastructure for high performance and expansion.

The Impact

The launch of Wapanda’s app was seamless, with Unthinkable ensuring on-time delivery and optimal performance. Adopting DevOps and CI/CD pipelines accelerated deployment, reducing update costs by 20% and improving release cycles by 5x. The real-time bidding model introduced a fresh approach to ride-hailing, earning positive feedback and increasing user adoption. Wapanda’s robust AWS infrastructure reduced operational costs and enhanced system reliability.

Conclusion

With the success of its launch, Wapanda is now working with Unthinkable to expand beyond Jersey City. The innovative fare-bidding model has positioned Wapanda as a promising player in the ride-sharing market. Looking ahead, the company aims to enhance the platform with AI-driven optimizations, improved analytics, and new city expansions.