The client wanted to build a quick-commerce model for MedTech.

However, unlike other quick-commerce industries, medicines came with multiple challenges:

• Certain medicines could not be delivered without prescription
• One medical store did not always have all the medicines available
• Delivery timelines would vary during peak hours and weekends
• Customers were getting uncertain delivery experiences when medicines had to be collected from multiple stores
  

We created a network of 500 medical stores within a 2 km radius.

Here’s how the system worked:

• Once a customer placed an order, the request was broadcasted to all nearby partnered medical stores.
• The first store that confirmed availability would accept the order.
• In cases where one store did not have the complete inventory, the remaining medicines were automatically sourced from other nearby stores.
• The system intelligently split the order across multiple stores to ensure complete fulfillment.

To make deliveries efficient, the rider received an optimized route map:

• The route started from the store farthest from the customer.
• It ended at the store closest to the customer’s delivery location.

This optimization ensured that by the time all medicines were collected, the rider was already near the customer, reducing the final delivery time significantly.

Since all stores were located within close vicinity, riders could typically collect medicines from multiple stores within five minutes before proceeding for delivery.

We also built a smart delay management system:

• If the algorithm detected that the rider needed to visit more than two stores, the customer automatically received a pop-up notification explaining that certain medicines were unavailable at a single store.
• The system then informed the customer about a possible delay of 5–7 minutes.

To make the experience transparent and reliable, we integrated Google APIs for:

• Real-time route optimization
• Live rider tracking
• Accurate delivery ETAs
• Dynamic delivery status updates

This combination of distributed inventory management, intelligent order splitting, route optimization, and real-time communication enabled us to successfully implement a quick-commerce model in the MedTech ecosystem despite inventory and regulatory challenges.

The system helped create a smoother quick-commerce experience for MedTech by:

• Improving medicine availability
• Reducing delivery confusion
• Rider route optimization
• Real-time customer communication
• Overall quick-commerce delivery experience for MedTech

As a result, we were able to build a reliable and scalable quick-commerce MedTech delivery ecosystem with predictable timelines and higher customer trust.