AI-Powered Custom Style Guidance Case Study

Challenge

To revolutionize personal styling, our client from Germany envisioned an AI-powered solution that provides hyper-personalized fashion recommendations aligned with your physical traits, simply by clicking or uploading a photo.

They wanted to create an AI solution that automatically detects facial features such as hair color, skin tone, and eye color, then provides hyper-personalized fashion recommendations. The client hired TatvaSoft to leverage our expertise in AI and computer vision to build an intelligent, intuitive image analysis platform that delivers fashion insights previously exclusive to professional stylists.

Key Challenges

The project our Germany-based client brought to us was ambitious, aiming to revolutionize the fashion industry using sophisticated AI solutions. However, several challenges arose:

Accurately analyzing users’ facial images and identifying physical traits such as gender, age, skin tone, hair color, eye color, and other facial accessories.
Generating simple yet precise color profiles using advanced image processing and clustering techniques.
Support real-time and batch image processing for both instant user feedback and backend scalability.
Delivering consistent and inclusive results across diverse user demographics, lighting conditions, and image qualities.
Offering personalized style recommendations by integrating facial and color traits with fashion principles like the 16-season color theory.
Providing a seamless, data-driven, and visually intelligent styling experience to enhance overall user engagement and satisfaction.

Expertise

Tools & Technology

ReactJS(PWA) • NodeJS • Python • React Native
Database

PostgreSQL
LLM Integrations

Chat-GPT 4o • OpenAI • OpenCV • MTCNN • Media-Pipe

Solution

TatvaSoft developed a PWA-based mobile application that analyzes user-uploaded facial images and delivers accurate, personalized style recommendations. The system uses advanced image processing and machine learning techniques to identify key facial traits such as skin tone, eye color, hair color, and more.

This intelligent styling software applies the 16-season color theory to create custom color palettes with corresponding RGB and HEX values, tailored to each user's natural features. To achieve this, we equipped the API-powered custom style guidance system with the following features:

Facial Color DetectionWhen a user uploads an image to the system, this feature identifies the user’s natural colors—such as eye color, hair color, and skin tone—by analyzing the image. It first segments the image into smaller regions, isolating each facial area, then applies advanced computer vision techniques to extract dominant hues. Representative colors from each region are identified using K-means and other clustering algorithms.
Demographic Recognition By leveraging AI models to analyze users' facial features, our custom style guidance system can estimate their age group and gender identity. These AI models use deep learning algorithms and are extensively trained on diverse, inclusive datasets. This approach helps avoid bias and improves accuracy across different lighting conditions and ethnicities.
Accessory IdentificationBy deploying real-time detection models like Mask R-CNN, this feature enables the system to identify and segment accessories even under varied lighting conditions or occlusion. Our AI-powered style guidance system supports diverse user contexts through batch processing and real-time detection.
Dominant Color Extraction This AI-powered styling system goes beyond facial analysis by extracting dominant color themes from the user’s clothes and accessories through whole-image evaluation. By integrating these colors into the user’s color profile, the system offers enhanced, personalized fashion recommendations.
Personalized styled Recommendations Based on the 16-season color theory, combined with facial detection features and demographic data, the system matches the user’s requirements to a specific season profile, such as warm autumn or cool summer, to provide personalized fashion recommendations. The AI models are pre-trained on highly curated fashion data and consider a wide range of user inputs, including fashion preferences and body shapes..

Result

TatvaSoft delivered a scalable and cost-efficient advanced AI solution that helped the client automate their styling process, including identifying facial features and offering highly personalized styling suggestions. As a result, user engagement and satisfaction rates increased, along with the overall user experience. Using an AI platform also enabled the client to create new opportunities for business growth and market expansion.