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Multichoice installer payments vs Picking & Packing app vs Fashionly

The problem, what was built, the stack and the outcome, next to each other.

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In common

  • Shared stack: none in common
  • Order: Picking & Packing app (2025 – 2026) → Fashionly (Apr 2026 – present)

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Multichoice installer payments ›

R5M+ paid to installers in the first six months

Picking & Packing app ›

A Kotlin warehouse app for fulfilment teams

Fashionly ›

Your style, elevated: an AI stylist that starts with what you own

At a glance

Role
Integration engineer
When
Delivered
Length
—
Status
Delivered
Type
Platform
Role
Lead, Smart Kitchen Co
When
2025 – 2026
Length
1 yr
Status
Delivered
Type
Mobile
Role
Founder / Lead Engineer
When
Apr 2026 – present
Length
7 mo so far
Status
MVP
Type
AI, Mobile, Web

The problem

Integrated the installer management system into Multichoice's payment process so installers are paid accurately and on time.
An Android app that drives picking and packing for warehouse and fulfilment operations.
Fashion-commerce recommendations usually optimise for another purchase without understanding what the customer already owns.

What was built

—
—
Fashionly grounds recommendations in the user's wardrobe, builds outfits from existing items and recommends products only where a genuine wardrobe gap exists. Khanya, a LangGraph stylist with about 15 typed tools, handles wardrobe access, catalogue search, saved looks and human-stylist bookings.

Stack

  • Payments integration
  • Kotlin
  • Android
  • Next.js
  • Kotlin
  • Supabase
  • LangGraph
  • MongoDB
  • SSE

Highlights

  • Processed over R5 million in installer payments within six months
  • Led architecture and development
  • Built in Kotlin for warehouse floor use
  • Khanya: a LangGraph tool-calling stylist with about 15 typed tools
  • MongoDB-checkpointed conversation memory and SSE streaming of tool progress and grounded product cards
  • Request-scoped Supabase clients with row-level security on every request

Infrastructure choices

—
—
  • Supabase with RLS
  • MongoDB checkpoints
  • SSE

Outcome

Over R5 million in installer payments processed within six months.
—
A working end-to-end MVP across web and Android: wardrobe management, catalogue discovery, conversational styling, saved looks and human-stylist booking.