How Errandd Automated Restaurant Dispatch and Eliminated 80% of Manual Driver Coordination

LocationIndia

SolutionCustom Food Delivery App

80%

Less Manual Dispatch

Automated

Route Optimizationg

Live

Real-Time Order Tracking

At-a-Glance

Errandd (Hyper-Local Food & Errand Delivery Startup)

Case Study

CHALLENGE:

As Errandd's daily order volume skyrocketed, their manual system of assigning drivers to restaurant pickups via phone calls collapsed.Food was getting cold, drivers were taking inefficient routes, and customer complaints were surging.

SOLUTION:

Intelegain built a sophisticated "Uber Eats" style platform featuring a custom algorithmic dispatch engine that automatically assigns the nearest available driver to an order and optimizes their route.

RESULTS:

The new platform eliminated 80% of manual dispatching tasks, drastically improved delivery times through automated route optimization, and restored customer trust with real-time GPS order tracking.

The Challenge: Before Intelegain

Errandd launched with a mission to provide hyper-local food and errand delivery for specific urban neighborhoods. Initially, their model was highly manual: a customer placed an order, an admin called a restaurant to place the order, and then called a driver to coordinate the pickup. This worked for the first hundred orders, but as volume scaled, the system imploded.

During peak lunch and dinner rushes, admins were overwhelmed. They couldn't manually calculate which driver was closest to which restaurant, leading to drivers crossing paths across the city while food went cold. Customers had no way of knowing when their food would arrive, resulting in a flood of "Where is my order? " calls that tied up the phone lines even further. Errandd needed an automated tech stack to survive their own growth.

Manual dispatching broke down completely during high-volume peak hours.

Inefficient driver routing resulted in cold food, angry customers, and wasted fuel.

Zero transparency for the end consumer regarding their order status or delivery ETA.

Why Errandd Chose Intelegain

Errandd required an agency that could build the entire ecosystem from scratch-fast. They chose Intelegain based on their proven ability to build complex, algorithmic logistics applications.

Algorithmic Expertise:

Intelegain possessed the technical capability to write custom dispatch algorithms that factor in driver location, restaurant prep time, and route traffic.

Tri-App Ecosystem Experience:

Proven experience building the requisite three interconnected apps (Customer App, Driver App, Restaurant Dashboard) seamlessly.

Scalable Cloud Backend:

The ability to design a backend capable of handling sudden, massive spikes in concurrent users and orders during meal times.

Implementation: The Intelegain Approach

Intelegain executed a full-stack digital transformation, moving Errandd from a manual phone-based service to a fully automated tech company.

Phase 1: Automated Dispatch Engine Design

The core of the project was the backend logic. Intelegain developed an algorithm that listens for new orders, estimates restaurant prep time, pings the GPS of all active drivers, and automatically assigns the pickup to the driver positioned to arrive exactly when the food is ready-eliminating wait times for both the driver and the food.

Phase 2: The Three-App Ecosystem Build

Intelegain rapidly developed three interfaces. The Restaurant Tablet App allowed kitchens to receive orders and tap "Ready." The Driver App provided turn-by-turn navigation via Google Maps. The Consumer App featured an intuitive menu browsing experience and secure payment gateways.

Phase 3: Real-Time Tracking & Launch

Using WebSockets, Intelegain ensured the Consumer App updated in real-time. Customers could now watch an icon of their driver moving along a map, entirely eliminating the need for customer service check-ins. The platform was successfully load-tested and launched to the app stores.

React Native (iOS/Android)Node.js & WebSocketsCustom Dispatch AlgorithmsStripe Payment Integration