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Aress OrderIt: Building an Intelligent Quick Commerce Delivery Platform with AI-Powered Optimization

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Posted on Feb 11, 2026
by Dilbagh Dhindsa ( Practice Head – AI and GenAI)

Aress OrderIt: Building an Intelligent Quick Commerce Delivery Platform with AI-Powered Optimization

Quick commerce has transformed customer expectations forever.

Today, customers don’t just want groceries delivered — they want them delivered in 10–20 minutes, with live tracking, instant updates, and seamless reliability. Behind the scenes, however, hyperlocal delivery is one of the most operationally complex industries to scale.

That’s exactly where Aress OrderIt comes in.

OrderIt is an intelligent delivery platform designed to solve the hardest problems in quick commerce:

  • Rider assignment at scale
  • Multi-order route optimization
  • Real-time tracking and customer visibility
  • Instant dispatch decisions powered by AI optimization

In this article, we explore how OrderIt is architected, what makes it different, and why optimization-first delivery systems represent the future of hyperlocal logistics.

Watch OrderIT Live in Action

The Quick Commerce Challenge: Why Delivery Operations Break at Scale

Quick commerce platforms face operational bottlenecks that grow exponentially with volume.

Unlike traditional e-commerce, where delivery timelines are measured in days, hyperlocal commerce operates in minutes. That creates three core challenges:

1. Rider Assignment Inefficiency

Most delivery systems still rely on simplistic assignment logic:

  • Assign the nearest rider
  • First-come-first-serve dispatch
  • Manual rider decision-making

This leads to:

  • Poor rider utilization
  • Increased delivery delays
  • Higher operational costs

2. Suboptimal Multi-Stop Routing

When riders handle multiple deliveries, routing often becomes heuristic or manual.

Riders choose delivery sequences themselves, causing:

  • Unnecessary detours
  • Delayed drop-offs
  • Inefficient batching

3. Lack of Real-Time Visibility

Customers today expect the same transparency as ride-sharing apps.

Without live tracking and push-based updates:

  • Customers lose trust
  • Support teams get overloaded
  • Operations cannot intervene proactively

OrderIt: An Optimization-First Delivery Platform

OrderIt was designed as a full-stack solution to address these challenges through three tightly integrated layers:

Customer Application

A mobile-first ordering experience with real-time delivery tracking.

Rider Panel

A dedicated interface for delivery partners to manage assignments and routes.

Backend Optimization Engine

A decision engine powered by Google OR-Tools.

OrderIt leverages AI-powered optimization solutions to solve rider assignment and routing problems in real time.

Together, these components enable OrderIt to deliver faster, smarter, and more scalable hyperlocal delivery operations.

Platform Overview: Hyperlocal Delivery Built for Speed

OrderIt is built using cloud-native platform engineering, enabling scalable, zone-based delivery operations with real-time decision-making across warehouses and rider networks.

Each warehouse is paired with a rider network so that pickup and delivery cycles remain ultra-fast.

The platform is designed around one principle:

Every delivery decision must be driven by real-time optimization, not guesswork.

Customer Application: A Seamless Ordering Experience

The customer-facing application is built for speed, clarity, and convenience.

Product Catalog Designed for Quick Browsing

Customers browse across structured categories such as:

  • Dairy
  • Fruits & Vegetables
  • Snacks
  • Beverages
  • Grocery
  • Household
  • Personal Care
  • Sweets

Each product includes:

  • High-quality imagery
  • Weight and size details
  • Discount badges
  • Fast category navigation
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Smart Order Placement Workflow

Once customers add items to cart:

  • The system detects delivery area
  • GPS coordinates identify the nearest warehouse
  • Total order weight is computed automatically

This weight becomes critical for downstream rider assignment.

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Real-Time Delivery Tracking

OrderIt provides customers with end-to-end visibility.

Order statuses flow through:

  • PENDING
  • ACCEPTED
  • PICKED_UP
  • DELIVERED

Push notifications are delivered instantly using Azure Web PubSub.

Rider Panel: Empowering Delivery Partners

The rider experience is just as important as the customer experience.

OrderIt includes a dedicated Rider Panel optimized for mobile devices.

Rider Login and Profile Management

Each rider profile includes:

  • Name
  • Vehicle type (Bike / Three Wheeler)
  • Assigned delivery zone
  • Performance rating

The interface is built for speed and safety, especially on iPhone devices with safe-area support.

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Instant Order Notifications

When a customer places an order:

  • The optimization engine selects the best rider
  • The rider receives a push notification in real time

The notification includes:

  • Item list
  • Distance to warehouse
  • Distance to customer
  • Estimated delivery fee
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Accept/Decline with Cascading Assignment

OrderIt introduces a major operational innovation:

Cascading Rider Assignment

  • Rider #1 is notified first
  • If declined, Rider #2 is instantly notified
  • No recalculation delay
  • Assignment happens in seconds

This eliminates dispatch bottlenecks completely.

Multi-Order Support with Route Re-Optimization

Unlike traditional one-order-per-rider systems, OrderIt enables:

  • Multiple active deliveries per rider
  • Dynamic route recalculation when a new order is added
  • Higher rider utilization

This improves throughput by up to 30%.

Backend Intelligence: The Optimization Engine at the Core

The true differentiator of OrderIt lies in its AI-driven backend.

Every order triggers a mathematical optimization workflow powered by Google OR-Tools.

1. Rider Assignment Optimization (Linear Programming)

OrderIt solves rider assignment as a Linear Programming problem.

The cost function considers:

  • Distance (70%)
  • Availability (20%)
  • Vehicle Match (5%)
  • Rider Rating (5%)

Instead of simple nearest-rider dispatch, the solver produces a ranked preference list instantly.

2. Route Optimization (Vehicle Routing Problem Solver)

For riders handling multiple deliveries, OrderIt solves a full VRP problem:

Inputs:

  • Rider location
  • Warehouse pickup point
  • Multiple customer destinations

Constraints:

  • Vehicle capacity
  • Maximum route distance

Outputs:

  • Optimal multi-stop delivery sequence

Results:

  • 15–25% reduction in distance traveled
  • 20–30% faster delivery times

3. Intelligent Order Batching

OrderIt uses spatial clustering to batch nearby deliveries:

  • Orders within 2 km radius grouped
  • Assigned to one rider
  • Route optimized automatically
  • Time-window constraints prevent delays

4. Real-Time Communication Layer

OrderIt eliminates polling completely through push architecture:

  • Riders receive assignments instantly
  • Customers get live status updates
  • Admin teams see real-time system broadcasts

Azure Web PubSub ensures millisecond-level responsiveness.

Fallback queues are stored in Redis.

Key Differentiators of OrderIt

OrderIt stands apart through:

  • Optimization-First Dispatch
  • Every decision is mathematically optimal, not heuristic.
  • Cascading Rider Assignment
  • Near-zero reassignment latency.
  • Multi-Order Routing Support
  • 30% higher rider efficiency.
  • Real-Time Push Architecture
  • No polling, instant visibility.
  • Modular Extensibility
  • Independent services for routing, batching, notifications.

OrderIt reflects how Aress approaches enterprise product engineering by building practical, scalable platforms that solve real delivery challenges, not just theoretical ones.

About Dilbagh Dhindsa

Practice Head – AI and GenAI

Dilbagh is a hands-on leader in Generative AI, AI/ML engineering, Data Science and software development. With over 20 years of International experience. He has developed groundbreaking AI and Generative AI solutions for global customers that helped solve complex business problems and optimize processes.


He had developed GenAI Accelerators for generating Sections of SoW(Statement of Work) using innovative metadata-driven dynamic chunk mapping. A US patent have been filed for the solution. Other GenAI Solutions included Secure Private GPT, an Email processor for license information, Recruitment tool for matching JD with resumes and chat.

Category: GenAI & Data Engineering

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