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Ventaw vs Fashionly vs ParcelNow

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

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In common

  • Shared stack: Next.js
  • Both kinds of work: Web
  • Order: ParcelNow (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

ParcelNow ›

On-demand parcel delivery with real-time tracking

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
Technical lead, Smart Kitchen Co
When
2025 – 2026
Length
1 yr
Status
Delivered
Type
Web, Platform

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.
Customer and operations dashboards with backend services for parcel lifecycles, tracking events and notifications, built for high-throughput transactional workflows.

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
  • Next.js
  • FastAPI
  • PostgreSQL
  • Redis
  • Docker

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
  • Next.js dashboards over FastAPI services
  • Live delivery updates through logistics and messaging integrations

Infrastructure choices

—
  • Supabase with RLS
  • MongoDB checkpoints
  • SSE
  • Docker-based development and deployment standards

Outcome

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