AŞO logo

Feature Detail

AI Outfit Planner

Personalized suggestions driven by occasion, wardrobe data, and style profile context.

Proof of Output

Inputs

  • • Occasion: Work meeting
  • • Weather / Climate: Warm, 29°C
  • • Dress code: Smart casual

Controls

SwapSaveAdd to favorites

Output

Look 1

Soft navy shirt + stone trouser + loafers

Look 2

Olive overshirt + tapered chino + sneakers

Look 3

Charcoal knit + straight trouser + derby shoes

Chosen look balances formal intent with warm-weather comfort and reuses high-confidence pieces from your history.

1. Problem

Most outfit choices fail because they are made manually each day without structured context (occasion, weather, inventory, fit, and preference data).

2. The AŞO System Solution

AŞO converts profile and wardrobe signals into a repeatable suggestion pipeline with swap/feedback loops and rule safeguards.

System Loop

Profile + Wardrobe + ContextPlanner EngineLook OutputFeedback

3. What It Actually Does

  • Generates occasion-specific looks from your wardrobe context.
  • Swaps suggestions without repeating prior item combinations.
  • Learns from likes and saved looks to improve future suggestions.
  • Falls back to rule-based logic when AI services are unavailable.

5. Plan Availability

Included in Wardrobe Pro and Wardrobe Exclusive. Lite includes limited daily suggestions.

Exact limits are configurable.

6. FAQ

Is this pure AI or rule-based?

Both. The code supports AI generation and a rule-based fallback for reliability.

Can I reject a suggestion and get another?

Yes. Swap endpoints are implemented and wired in the app.

Do I need to digitize my wardrobe first?

You can start early, but planner quality improves as your wardrobe inventory and profile become more complete.

Does AŞO use my photos?

AŞO uses wardrobe and profile data to generate suggestions. Photo usage follows your account permissions and privacy controls.

Can I control formality and color preferences?

Yes. Occasion context, formality, and profile preferences are part of planner input and influence output directly.

How does feedback change future suggestions?

Likes, saves, and swaps are captured as preference signals that bias future recommendations toward your proven choices.

What happens when AI is unavailable?

AŞO automatically uses its rule-based fallback so planning remains usable and decisions stay consistent.