WardrobeAI — a curated clothing subscription service sourcing from small businesses and boutique brands, with AI-powered style matching, fit feedback loops, and on-demand design/tailoring.
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OpenClaw Agent b177fcccc0 Consolidated fix: profile fetch, affiliate env var, CORS lockdown, auth TODO
Combines fixes from PRs #34 and #35 into a clean single branch.

## Profile fetch fix (was PR #34)
- CuratedBox.js: Fetch user profile from /api/profile/:userId before
  generating box. Use actual user preferences (colors, styles, budget)
  instead of hardcoded placeholders.

## Affiliate env var fix (was PR #35)
- init-db.js, server.js: Read AMAZON_ASSOCIATE_ID from env var, fall
  back to 'greybeardhold-20'. Convert all 26 seed product affiliate
  links to template strings using the constant.
- .env.example: Add AMAZON_ASSOCIATE_ID configuration example.

## CORS lockdown
- server.js: Restrict CORS to specific origins (localhost:3000,
  wardrobe.scoble.me) instead of wildcard '*'.

## Auth TODO
- CuratedBox.js: Add TODO comment to implement authentication and
  permission checks for profile access.

## Style validation fix
- server.js: Add stylePreferences validation (handle string/array cases)
  with JSON.parse fallback in the /api/box endpoint.

## Minor fix
- server.js: Fix leading space in Pact Women's Cotton Cardigan title.
2026-05-02 22:49:12 -07:00
.openclaw Option D: initial workspace commit with memory architecture 2026-04-25 13:51:53 -04:00
memory Option D: memory rewrite — daily notes updated 2026-04-25 15:49:35 -04:00
wardrobe-ai Consolidated fix: profile fetch, affiliate env var, CORS lockdown, auth TODO 2026-05-02 22:49:12 -07:00
.gitignore Merge PR #35: Amazon affiliate env var + MVP core 2026-05-02 17:24:06 -07:00
AGENTS.md Option D: initial workspace commit with memory architecture 2026-04-25 13:51:53 -04:00
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DREAMS.md Option D: memory rewrite — daily notes updated 2026-04-25 15:49:35 -04:00
HEARTBEAT.md Option D: initial workspace commit with memory architecture 2026-04-25 13:51:53 -04:00
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WardrobeAI

Clothes from real designers. Picked for you. On your budget.

WardrobeAI is a curated clothing subscription service that sources from small businesses and boutique brands. We learn your personal style through a real conversation (not a multiple-choice quiz), match pieces within your monthly budget, and get better with every box based on your feedback.

The Problem We're Solving

For customers:

  • Shopping is overwhelming — thousands of options, no curation
  • Small designers are hard to find (buried on Etsy, hard to discover on Instagram)
  • Mass-market subscriptions feel generic — same brands everyone else wears
  • "Style quizzes" don't capture the nuances of your body and life
  • The feedback you give doesn't seem to change what you get

For small designers:

  • Hard to reach customers without massive ad budgets
  • Wholesale buyers require large minimum orders
  • No direct feedback on why items don't sell

Our Approach

What Others Do What We Do
Source from mass-market brands (Stitch Fix, Nordstrom) Source from small businesses and boutique designers first
Per-item pricing ($40-80 per piece) Monthly budget you choose ($100 or $250)
Multiple-choice style quiz Real conversation — style interview with a human feel
"Style Shuffle" that never learns Structured feedback loop that actually improves
One-size-fits-all "Invariants" — your hard lines, honored (no florals, no synthetics, etc.)
Off-the-rack only AI design-on-demand: "I want this shape in that fabric" — custom made

Product Tiers

Essential — $100/mo

  • 3-5 clothing items per month
  • From small businesses and boutique brands
  • Style interview and feedback loop included
  • Shoes, bags, jewelry available as add-ons

Signature — $250/mo

  • 4-8 clothing items per month
  • Higher-end boutique brands
  • Early access to new designers
  • Concierge-level style interview

Custom — Variable

  • You set the budget
  • You choose the components (clothing only, or full wardrobe)
  • Custom frequency (monthly, quarterly, etc.)
  • Priority access to AI design-on-demand

Market Opportunity

  • $7 billion global fashion subscription market
  • Growing at 6.1% CAGR (2025-2034)
  • No incumbent dominates the "small business boutique" niche
  • Stitch Fix is mass market; Rent the Runway is rental; no one is budget-capped with boutique curation

Competitive Landscape

Company Model Our Differentiation
Stitch Fix ($1.6B market cap) AI + human stylist, mass brands We source from small businesses; we have budget caps
Wantable Curated edits, $20 styling fee We have a real conversation, not a quiz; our feedback loop learns
DailyLook Premium styling, $40 styling fee We start at $100/mo, not premium; we honor hard constraints
Dia & Co Plus size niche We're size-inclusive but not niche-restricted
Rent the Runway Rental subscription We sell, not rent; you keep what you love

The niche we own: Small business curation with budget caps and real learning.

Technology Stack

  • Frontend: Next.js (React), Tailwind CSS, mobile-first
  • Backend: Node.js or Python (FastAPI), PostgreSQL + Redis
  • AI/ML: Python service for curation; LLM integration for style interview and invariants parsing
  • Payments: Stripe (subscription billing)
  • Hosting: Vercel (frontend) + Railway/Fly.io (backend)
  • Analytics: Umami (self-hosted, already deployed)
  • Infrastructure: Storj for static assets, potential 3PL for warehousing (Phase 2)

Repository Structure

wardrobe-ai/
├── brand/          # Brand identity, positioning, customer personas
├── business/       # Pricing, financial model, vendor targets, roadmap
├── engineering/    # Architecture, curation engine, tech docs
├── legal/          # Compliance, terms, policies
├── marketing/      # Social strategy, content calendar, viral playbook
├── operations/     # Return logistics, shipping, warehouse transition
├── product/        # Style interview, feedback system, invariants, landing page
├── research/       # Competitive analysis, market data
└── site/           # Landing page source (Astro SSG)

Roadmap

Phase 0: Foundation (Months 1-2)

  • Brand identity finalized
  • 10-20 customer discovery interviews
  • 5-10 vendor partners identified
  • Landing page + waitlist live
  • Legal structure + insurance

Goal: 50+ waitlist signups, 3+ vendor commitments

Phase 1: MVP (Months 3-5)

  • 20 founding customers (friends, family, early signups)
  • Essential tier only ($100/mo)
  • Manual curation with AI assistance
  • Web app: style interview + feedback
  • Manual returns processing

Goal: 60%+ keep rate, NPS 40+

Phase 2: Growth (Months 6-9)

  • Signature tier launch ($250/mo)
  • AI curation engine v2
  • TikTok + Instagram content machine
  • Referral program
  • 100 subscribers

Goal: 65%+ keep rate, 10%+ MoM organic growth

Phase 3: Scale (Months 10-18)

  • 500+ subscribers
  • AI design-on-demand pilot
  • Warehousing or 3PL transition
  • 30+ active vendors
  • Mobile app

Goal: 70%+ keep rate, positive unit economics

Phase 4: Expansion (Months 18-36)

  • 2000+ subscribers
  • Men's clothing vertical
  • Plus-size specialization
  • AI design-on-demand full launch
  • Potential Series A or profitable bootstrapping

Issues & Project Management

All work is tracked via Forgejo Issues.

Labels:

  • market — Market research, competitive analysis, customer personas
  • feature — Product features and design
  • engineering — Technical implementation and architecture
  • business — Pricing, financials, vendor partnerships
  • legal — Compliance, terms, policies
  • improvement — Documentation and process improvements

Why This Matters

Fashion is personal. It's how we present ourselves to the world. But the current options are either overwhelming (do-it-yourself shopping) or generic (mass-market subscriptions).

We believe there's a middle path: curated discovery from real designers, within a budget that makes sense, with a system that actually learns what works for you.

Supporting small businesses while helping people feel like themselves. That's WardrobeAI.


Work in progress. Phase 0 — validating demand and building the foundation.

Commit signing enabled: Sat May 2 12:47:38 PM PDT 2026