15–20s
Evolving styling companion / Product dossier
case 03OUTFITTED
It inherits the knowledge, reasoning, and role collaboration of FashionAgent, then compresses them into a product that is faster, lighter, and more sustainable in repeated use.From need input to outfit generation, evaluation, visual preview, and growth archive, OUTFITTED already forms a product loop that can be experienced, reused, and continuously evolved.
<3s
¥0.1–0.3
Value Proposition
An evolving expert styling companion
Product definition
Not a one-off styling answer machine, but a fashion service system that keeps understanding the user, organizing professional knowledge, generating comparable directions, and gradually accumulating a personal style archive through repeated use.
Demo
Product Demo
From need input to recommendation, visual preview, evaluation feedback, and growth archive, OUTFITTED already forms a complete product loop.
Capability Chain
Turning capability into service
Service framing
This is not a pile of disconnected features. Need interpretation, professional recommendation, controllable collaboration, visual generation, and history tracking are compressed into one real service chain that actually runs.
Product Evolution
From FashionAgent to OUTFITTED
The real change is not the name, but the compression of a research-heavy multi-agent prototype into a product that is lighter, faster, more visual, and closer to real use.
Current maturity
It is already a product capable of a full demo and a usable main flow, but it stays honest: some parts are already usable, while others still belong to the lightweight version or the next stage.
Current state
lightweight but usable
Working but still lightweight
The design follows LangGraph-style orchestration, but runtime still uses a lightweight sequential graph. PostgreSQL and Redis have interfaces and fallback, not a production-grade setup yet.
To stabilize
still converging
Visual layer still stabilizing
Virtual try-on is usable, while garment swap is still more of a preview path than precise editing. Trend retrieval also still leans on compiled local JSON.
To complete
engineering in progress
Engineering still incomplete
True SSE streaming, cancellation, prompt caching, Redis result caching, image URL caching, and stronger monitoring remain to be finished.
Growth & Companionship
Beyond styling, know yourself better
OUTFITTED ultimately serves more than today’s outfit choice. Through repeated comparison, preview, feedback, and memory, it helps users read their own preferences, states, and changes more clearly.
Companionship
The service relationship extends beyond one output.
Understanding
The system gradually learns not only to answer, but to understand the user.
Growth
Style exploration shifts from result-chasing to the ongoing formation of self-expression.