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

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Ventaw ›

Secure, isolated environments for developer workloads

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
In progress
Length
—
Status
In progress
Type
Platform, Web
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

Environment provisioning, session management and resource monitoring, designed for security, multi-tenancy and concurrent workloads.
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.
—

Stack

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

Highlights

  • Next.js management interface
  • FastAPI orchestration APIs
  • 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
—

Outcome

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