Muhammad Adil Malik

Full Stack Developer

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Mobile

Bevoe: Community-Driven Local Shopping

Lead Mobile Developer / Architect202410 monthsClient: SAS BEVOE

A mobile application for exploring great local deals specially curated for you, ensuring a seamless and hassle-free community shopping experience.

<200 ms

Search Speed

2000+

Local Users

75+

Partner Stores

The challenge

We start with the real problem

Clear problem framing first — then a solution designed to remove friction for users and operators.

Problem

What was broken

Finding unique local products or time-sensitive community deals often requires physical exploration or browsing fragmented local social media pages. This is inefficient for both shoppers wanting convenience and local businesses trying to reach a digital audience without major marketing budgets.

Solution

How we fixed it

We developed Bevoe, an intuitive mobile ecosystem featuring geolocation-based deal discovery, dynamic product catalog browsing, and store-specific code lookups. Shoppers can instantly view available inventory, compare local offers, and shortlist favorite items for their next community shopping trip.

Deep dive

How this product was built

Full written walkthrough of the system — architecture decisions, product surface, and operating model.

Read the full deep dive

2 detailed sections · architecture, product surface, and ops

Bevoe is a hyper-local shopping and deals discovery platform designed to connect community members with unique local businesses and offers. Users simply enter their location or a specific store code to explore curated selections of retail items, fashion, and services in their immediate area. The platform streamlines the local product search, allowing users to browse rich product catalogs and shortlist deals, making local commerce more accessible and community-focused.

01

Simplifying Local Deal Discovery

In a market dominated by major online retailers, independent local businesses often struggle to make their unique products digitally discoverable to their immediate community. Bevoe was built to address this disconnect, transforming the community shopping experience by bringing the local high street into a modern mobile app.

The platform removes the hassle of physical browsing. Users simply enter their location—such as a specific street or neighborhood—and the app dynamically populates a list of great local deals curated specially for them. Whether it's the latest fashion, artisan goods, or unique tech items, Bevoe makes local shopping effortless.

Shoppers can dive deep into detailed product catalogs, viewing high-resolution images, descriptions, and prices. This allows users to make informed purchase decisions and efficiently plan their shopping trips, ensuring they don't miss out on local gems.

02

Empowering Local Retailers with Targeted Reach

For local retailers, Bevoe acts as a powerful digital storefront. By listing their products and offers, stores gain direct access to motivated shoppers in their area, significantly increasing their visibility and reach without the need for complex digital marketing strategies.

The application includes powerful features like store codes, enabling retailers to run exclusive, hyper-targeted campaigns for specific community events or repeat customers, further strengthening community engagement.

Capabilities

What the product delivers

Practical features users and operators actually rely on.

Location-based deal discovery engine.

Store-specific code lookup for exclusive community offers.

Detailed product catalog showcase with image galleries.

Personalized product shortlisting and favorites management.

Real-time deal availability updates.

Architecture

Built to hold up under real use

Stack and system choices that keep the product reliable as usage grows.

  1. 01

    React Native mobile application architecture providing a responsive and high-performance cross-platform shopping experience.

  2. 02

    Node.js / Express backend API layer managing store inventories, deal curation logic, and search index updates.

  3. 03

    PostgreSQL relational database for efficient product catalog management, store information, and geospatial data indexing.

  4. 04

    Advanced geospatial filtering algorithms enabling real-time distance calculations and accurate local deal prioritization.

  5. 05

    Content Delivery Network (CDN) integration for fast loading of high-quality product imagery.

Delivery

Hard problems, concrete fixes

Every serious product hits constraints. Here is what we solved.

Challenges

  • Managing real-time synchronization between disparate store inventories and the centralized platform.
  • Optimizing product search and filtering across thousands of localized inventory items.
  • Designing an experience that balances store-specific catalog browsing with discovery of nearby deals.

Technical solutions

  • Implemented automated inventory update pipelines and standard product schema APIs for easy retailer integration.
  • Engineered robust PostgreSQL search aggregation queries with text indexing and faceted filtering.
  • Developed an adaptive UI that provides seamless navigation between a 'Deals Map' view and structured 'Store Catalogs'.

Impact

Business outcome

Results that matter after launch — not just features shipped.

Bevoe successfully connected dozens of local retailers to an engaged digital audience, increasing store foot traffic and local product sales, while providing users with a convenient way to support and discover their community's unique offerings.

  • Streamlined hyper-local product discovery for community members.
  • Increased visibility and customer reach for participating independent retailers.
  • Improved conversion rates for store-specific community deals.

Stack

Technologies used

Tools chosen for the product — not a resume keyword list.

React Native
Node.js
Express
PostgreSQL
Geospatial APIs

Next step

Have a similar problem to solve?

Tell me what is broken in your product or workflow. I will reply with a clear take on approach, timeline, and whether I am the right fit.