BEYON. AI-Assisted Mobile Development Journey. iOS & Android | From Scratch to Production. 

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iOS & Android  |  From Scratch to Production

"AI is not just a coding tool — it is a development accelerator"

Lab-Grown Diamond Jewellery  |  Premium E-Commerce Mobile Apps  |  GitHub Copilot & Claude

BEYON | AI-Assisted Mobile Development. 2. Executive Summary. 

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The Beyon mobile apps (iOS & Android) for a premium lab-grown diamond jewellery brand were built from scratch using AI-assisted development (GitHub Copilot & Claude). What would traditionally require 4-6 developers over 3-4 months was achieved by a 2-person team in approximately 5 weeks.

KEY INSIGHT:  ~93% effort reduction  |  ~4x faster delivery  |  Zero critical vulnerabilities

BEYON | AI-Assisted Mobile Development. 3. Project Overview & Architecture. 

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Premium lab-grown diamond   jewellery e-commerce brand
   Full-featured mobile apps   (iOS & Android)
   Zara-inspired design: minimal,   white, image-dominant
 Project Goals:   1. Build from scratch using AI   2. Mirror functionality across      iOS & Android   3. Integrate with SFCC via AWS   4. Production-ready in weeks

Language: Swift UI: SwiftUI Architecture: MVVM State: Combine (Published) Navigation: NavigationStack Images: AsyncImage / SDWebImage Network: URLSession Payment: JusPay (CocoaPods)
 Flow:   SwiftUI Views       ↓   ViewModels (ObservableObject)       ↓   Service Layer → API

Language: Kotlin 2.0 UI: Jetpack Compose Architecture: MVVM / Clean State: StateFlow DI: Hilt Navigation: Navigation Compose Images: Coil Network: OkHttp + Retrofit Payment: JusPay HyperSDK
 Flow:   Compose Screens       ↓   ViewModels (hiltViewModel())       ↓   NetworkManager → ApiService

BEYON | AI-Assisted Mobile Development. 4. AI-Driven Development Model. 

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GitHub Copilot   Code generation, API integration, debugging Claude (Antigravity)   Initial iOS UI generation Roo Code   Security vulnerability scanning

PHASE 1 (Failed): Large bulk prompts   Modified multiple files → Introduced new bugs → Unstable output
 PHASE 2 (Success): Focused, scoped prompts   One module at a time → One issue at a time → Stable, controlled fixes

"Create a complete iOS/Android application with clean, scalable architecture..." "Integrate backend same as MIA app, UI should remain unchanged" "Enhance UI to premium and minimal luxury jewellery design" "Optimize PDP loading — load critical data first, defer remaining"

BEYON | AI-Assisted Mobile Development. 5. Development Journey — iOS & Android. 

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MIA iOS as reference
Copilot for API work

Home, PLP, PDP, Cart
Wishlist, Account, Payment

Auth, Home, PLP, PDP
Wishlist, Cart, Checkout
Orders, Profile

Complete backend APIs
Request/response mapping
Repository pattern

Fixed flickering states
Corrected identifiers
Accurate delivery msgs

Dedicated payment activity
Window/notch handling
Stabilized SDK

Custom header/footer
Grid & list views
Diamond wishlist icon

Progressive loading
Instant perceived load
No heavy loaders

KEY LEARNING:  Bulk prompts failed → Module-by-module with issue-by-issue fixes = Success

BEYON | AI-Assisted Mobile Development. 6. Core Features & Backend Integration. 

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Dynamic sections, banners, featured products

Grid/list views, filters, pagination, search

Images, price breakup, karat details, specs

Add/remove, serviceability, delivery, orders

Product catalog (PLP/PDP)   User authentication (OTP)   Cart & Wishlist operations   Order & Payment processing   Address CRUD, Serviceability   Multi-currency support

1. Perform action in app   2. Check AWS logs   3. Verify in SFCC Business Manager
   Paste logs → Copilot identifies   whether issue is FE / AWS / BE

BEYON | AI-Assisted Mobile Development. 7. UI/UX Premium Experience & Performance. 

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Zara-inspired editorial aesthetic   Minimal, white backgrounds   Image-dominant layouts   Near-zero corner radii   Premium typography & spacing   Luxury jewellery brand feel

Custom header, footer, tab bar   Grid & list toggle in PLP   Diamond-style wishlist icon   Enhanced PDP: price, karat, specs   Edge-to-edge display support   Device-specific fixes (notch, bar)

Phase 1 (Instant):   Product Image + Name + Price
 Phase 2 (Background):   Remaining specs, reviews, related
   ✅  Instant perceived loading

Basic product name + image only   No price breakup or karat details   Missing screens/flows  |  Too minimal for business

Rich PDP with all product details   Premium typography & spacing   Complete commerce flows  |  Luxury brand experience

BEYON | AI-Assisted Mobile Development. 8. Payment Integration & Security Hardening. 

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Integration: CocoaPods (Podfile) Challenge: Payment not working — missing Pod setup Fix: Installed required pods → Payment working Side Effect: Other modules broke → Re-fixed via prompts

Integration: Maven (maven.juspay.in) Challenge: UI breaking, notch/status bar overlap Fix: Dedicated payment activity + window handling Result: Reliable payment flow across devices

RESULT:  Zero Critical Vulnerabilities  |  FE issues fixed by Copilot  |  BE issues guided by Copilot

BEYON | AI-Assisted Mobile Development. 9. Challenges, Learnings & Best Practices. 

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Module-by-module, issue-by-issue approach

Extensive real-device testing, targeted fixes

Dedicated activity, careful dependency mgmt

Shared endpoints with Copilot, verified each

1. Module-by-module development 2. Issue-by-issue focused fixes 3. Rapid UI generation (hours, not weeks) 4. AI debugging (paste logs → analysis) 5. Iterative security scan + fix cycles

1. Large bulk prompts — unstable output 2. Fixing multiple issues at once 3. Assuming AI handles dependencies 4. Skipping validation — must test on device

BEYON | AI-Assisted Mobile Development. 10. Effort Comparison — The Big Picture. 

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BEYON | AI-Assisted Mobile Development. 11. Post-Deployment & Conclusion. 

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PAN Card Pop-up for Already-Verified Users

Bug: PAN verification shown again for verified users (cart > ₹2L) Root Cause: Verification was session-based instead of user-based Fix: Added isPanVerified flag on login (MIA pattern) via Copilot

QA finds bug → Dev scopes prompt → Copilot fixes → Validate on device

Two production-ready mobile apps (iOS + Android)   Built from scratch using AI-assisted development   Premium luxury-brand user experience   Complete e-commerce functionality   Robust security (zero critical issues)   Optimized performance (progressive PDP loading)   All in ~5 weeks with 2-person teams

Apply AI approach to new product lines   Expand AI to automated testing & monitoring   Scale methodology across the organization   AI-assisted deployment & CI/CD optimization

Structured prompts + validation = successful delivery  |  This approach can be scaled for future projects

Thank You. BEYON — AI-Assisted Mobile Development. 

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