LOOK 01 · 晨间通勤
Morning Commute · Structured & Effortless Balance
Heavyweight Silk Blouse + Wool Wide-Leg Trousers + Minimalist Leather Bag
Client: Ms. Lin · Preference: Warm Grey / Minimalist
Product overview
Client Styling & Inventory Assistant for Womenswear Boutiques
Shadow Garment
Demo · Early Recruitment
Help womenswear boutiques style the next outfit for regular clients.
Combine regular clients' known preferences with in-store inventory to produce complete, high-confidence outfit styling for boutiques and showrooms. Eliminate repetitive fitting friction and memory lapses.
01 / EDITORIAL
Curated Looks: From a Single Piece to Complete In-Store Moments
Not cold random item mashups, but grounded in the boutique owner's curation logic. We integrate VIP favorite tones with seasonal arrivals into warm, wearable looks with real living context.
LOOK 02 · 周末画廊
Weekend Gallery · Artistic Texture Layering
Deconstructed Knit Vest + Pleated Midi Skirt + Matte Square-Toe Ankle Boots
Client: Founder Zhang · Preference: Asymmetric / Cool Tea Tone
LOOK 03 · 私域晚宴
Private Evening · Refined Semi-Formal
Satin Cami Dress + Fluid Tailored Blazer + Strappy Heels
Client: Ms. Chen · Preference: Ink Black / Subtle Sheen
02 / FEATURES
How it helps
01
Client Preference Memory
Systematically capture silhouette tastes, taboo tones, and lifestyle scenes so newly joined staff can serve VIP clients seamlessly.
02
In-Store Inventory Linkage
Assemble curated looks strictly from current seasonal SKUs, preventing broken sizes and unavailable recommendations.
03
Private Domain Visual Cards
Generate tastefully designed styling look cards with one click, tailored for 1-on-1 WeChat chat and social moments sharing.
04
9:16 Dynamic Motion Preview
Simulate walking gait and natural drape of silk and wool, building outfit excitement before clients visit the store.
03 / SCENARIOS
Use Cases
01
Multi-Brand & Designer Boutiques
High average order values and unique pieces require bespoke total styling proposals to nurture VIP client loyalty.
02
Bespoke & Independent Studios
Founders have limited time; digital styling tools empower floor stylists to reproduce the founder's aesthetic standards.
03
High-Ticket Clienteling & Social Commerce
Move beyond spamming isolated item photos to sharing contextual full-outfit stories that wake dormant clients and drive store appointments.
06 / Questions
Frequently Asked Questions
Clear answers regarding features, compatibility, and privacy
What stage is Shadow Garment currently in, and how can I join the demo?
Shadow Garment is currently in the Demo and founder interview validation stage. We are onboarding a limited number of womenswear boutiques, multi-brand showrooms, and bespoke studios. After submitting your boutique info via "Request Demo", our team will connect with you via WeChat to schedule a 1-on-1 walkthrough.
What information is required to apply, and will my store data be collected?
Never. We only ask for your contact WeChat ID, city, and approximate store scale to personalize the demo flow. We never ask for client books, order logs, inventory credentials, or financial information.
Are outfit recommendations purely random AI outputs, or can owners adjust them?
Boutique founders always retain aesthetic control. Shadow Garment generates outfit proposals grounded in seasonal in-stock SKUs, allowing stylists to swap pieces, accessories, or palettes with one click while capturing feedback for continuous learning.
Does Shadow Garment require studio lighting or green-screen setups?
No. Shadow Garment is optimized for lean boutiques. It accepts standard mobile flat-lays, mannequin photos, and white-background supplier lookbook shots without costly studio rentals or full-time model shoots.
How soon will I be contacted after applying?
We typically respond via WeChat within 24 hours on business days. To ensure tailored discussions and quality feedback, we limit 1-on-1 walkthroughs to five stores per week.
“According to Software Engineering Research, specialized AI agents and workflows reduce operational overhead and increase task accuracy when integrated with explicit boundaries. Studies show that focused tools outperform monolithic systems in real-world environments.”