AI-Powered Body Measurement & Fit Recommendation Platform for Tailored Shirts
Industry
Fashion-Tech (AI SaaS)
Growth Stage
Pre-Seed
What we did
Product Development, eCommerce Integrations, AI & Computer Vision
Client Background
The Client is a leading AI Fashion-Tech company building computer vision solutions for the online apparel industry. Their vision was to eliminate size uncertainty in online fashion by enabling shoppers to receive accurate tailored shirt recommendations using nothing more than their smartphone camera.
The objective was to build a plug-and-play SaaS platform that any ecommerce business could integrate into its storefront regardless of whether it was built on Shopify, WooCommerce, or a custom platform. Rather than relying on manual measurements or traditional size charts, the platform would use AI to calculate precise body measurements from short mobile video captures before recommending the most appropriate tailored shirt size.
The platform consists of multiple integrated components including a browser-based body capture experience, an AI reconstruction pipeline, a merchant management platform, recommendation services, and ecommerce integrations that allow retailers to deploy the fitting experience with minimal setup.
It supports four distinct user types:
Platform administrators oversee merchant onboarding, subscriptions, AI infrastructure, and platform-wide operations.
Merchants configure their stores, upload brand-specific size charts, manage products, and monitor measurement history and recommendations.
Store administrators manage catalog mappings, customer reports, and sizing configurations across their ecommerce storefronts.
Online shoppers complete guided body scans using their smartphone browser and receive personalized tailored shirt recommendations within minutes.
Challenges
Size and fit uncertainty remains the leading cause of apparel returns in ecommerce, particularly for tailored garments where collar, shoulder, sleeve, and chest measurements must be highly accurate. Unlike casual clothing, even a small measurement error can make a tailored shirt uncomfortable or completely unwearable.
This introduced several technical challenges.
Measurement accuracy required deriving true three-dimensional body measurements from a standard smartphone camera without relying on specialized hardware or wearable sensors.
Capture consistency had to account for varying lighting conditions, clothing bulk, device positioning, camera angles, and user posture while ensuring non-technical shoppers could complete the scanning process in less than two minutes.
Quality validation needed to identify poor lighting, incomplete body visibility, cropped limbs, incorrect camera distance, or improper positioning before processing began, preventing wasted GPU resources and failed recommendations.
Recommendation flexibility required supporting dozens of merchant-specific size charts while intelligently resolving conflicts between garment dimensions such as chest, neck, shoulders, and sleeve length.
Privacy compliance demanded secure handling of biometric video data, encrypted transmission, temporary storage, automatic deletion after processing, and compliance with GDPR and BIPA requirements.
The objective was to replace unreliable size estimators with a production-ready AI platform capable of generating highly accurate body measurements, personalized fit recommendations, and seamless merchant integrations through a scalable SaaS architecture.
Implementation
Branding
Technical Architecture
The platform is built on a cloud-native architecture designed specifically for AI-powered body measurement processing. The merchant-facing backend is developed using Node.js, NestJS, and TypeScript with PostgreSQL and Prisma ORM managing merchants, size charts, subscriptions, customer measurements, and recommendation history. The browser-based fitting experience runs entirely on-device using getUserMedia and WebRTC alongside MediaPipe Tasks Web compiled with WebAssembly (WASM) and accelerated through WebGL, allowing real-time body landmark detection without requiring a native mobile application. AI processing services are built using Python, FastAPI, and PyTorch running on GPU-enabled AWS EC2 instances. Supporting infrastructure includes Redis and BullMQ for distributed processing queues, Amazon S3 for secure temporary storage, CloudFront for asset delivery, WebSockets for live processing updates, and Docker for containerized deployments with CI/CD.
Deployment Topology
Shoppers access the fitting experience directly from the merchant's ecommerce store using their mobile browser. Body landmarks are detected locally during capture while validated multi-angle images are securely uploaded to Amazon S3 using signed URLs. BullMQ queues distribute processing requests across GPU workers where the reconstruction pipeline generates three-dimensional body measurements before returning personalized size recommendations to the backend. Throughout processing, WebSocket connections stream real-time progress updates back to the shopper while merchants access recommendations and measurement history through the management dashboard.
Core Feature(s) Modules
Dynamic page and content management. A form-based system that puts full control of all site content in the client's hands. Homepage, service pages, FAQs, images and more, all editable without touching a single line of code. New dynamic pages can be spun up entirely in-house.
Lead management with built-in CRM. Captured leads flow directly into an integrated CRM. Multiple team members can be added with role and permission-based access, so everyone knows exactly what they own, and leads don't fall through the cracks.
Live Google Analytics integration. Real-time website performance data pulled directly into the admin dashboard. No switching tabs, no logging into separate tools.
In-platform SEO control. Meta details, on-page SEO, all editable from within the panel. The team doesn't need an SEO agency on retainer to make basic optimisations.
Dynamic 301 redirections. Admins can configure and manage 301 redirects on their own. URL changes don't have to mean losing link equity anymore.
Dynamic form builder. Custom forms can be designed and mapped to specific pages. Data capture adapts to the service, rather than forcing every enquiry into the same generic fields.
Newsletter capture and portability. Subscriber emails are stored in the platform database and synced to the email marketing tool. The retained master list means the client can switch email providers without losing a single subscriber.
Data Model & Access Control
The platform's PostgreSQL database is designed around a multi-tenant SaaS architecture supporting merchants, products, size charts, measurement records, recommendations, subscriptions, and processing jobs. Prisma ORM manages schema relationships and migrations, while UUID primary keys provide distributed scalability across the platform.
Each merchant maintains completely isolated sizing configurations, product mappings, and recommendation data, allowing multiple apparel brands to operate independently from a shared infrastructure. Merchant size charts are stored as structured JSON with configurable tolerance bands, enabling the recommendation engine to support different sizing standards without modifying application logic.
Authentication is secured using JWT-based authorization, ensuring merchants and administrators can only access resources belonging to their own organization. Processing status is streamed securely through WebSockets while signed URLs provide temporary access to uploaded scan files during AI reconstruction.
Biometric privacy is enforced throughout the processing pipeline. Body images are encrypted both in transit and at rest, uploaded temporarily to Amazon S3, and automatically deleted immediately after body measurements are generated. Only the derived numerical measurements persist within the database, supporting GDPR and BIPA compliance while minimizing long-term biometric data storage.
The Outcome
The outcome is an intelligent AI-powered virtual fitting platform that transforms how shoppers purchase tailored clothing online. Customers receive precise body measurements and personalized shirt recommendations directly from their smartphone, eliminating guesswork while improving purchase confidence.
For merchants, the platform reduces sizing-related returns, simplifies onboarding through plug-and-play ecommerce integrations, and delivers a scalable subscription SaaS solution capable of serving multiple fashion brands through a single AI-powered infrastructure.
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