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Fashionly vs Picking & Packing app

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

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In common

  • Shared stack: Kotlin
  • Both kinds of work: Mobile
  • Order: Picking & Packing app (2025 – 2026) → Fashionly (Apr 2026 – present)

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Fashionly ›

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

Picking & Packing app ›

A Kotlin warehouse app for fulfilment teams

At a glance

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

The problem

Fashion-commerce recommendations usually optimise for another purchase without understanding what the customer already owns.
An Android app that drives picking and packing for warehouse and fulfilment operations.

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.
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Stack

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

Highlights

  • 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
  • Led architecture and development
  • Built in Kotlin for warehouse floor use

Infrastructure choices

  • Supabase with RLS
  • MongoDB checkpoints
  • SSE
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Outcome

A working end-to-end MVP across web and Android: wardrobe management, catalogue discovery, conversational styling, saved looks and human-stylist booking.
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