Challenge
A renowned fashion industry player in the USA sought to provide a novel experience for its clients by
leveraging AI-powered style recommendations. The goal was to transform how users interact with their
wardrobes, offering intelligent outfit suggestions, celebrity-inspired styling, and a smooth digital
closet experience. The fashion industry lacked an advanced AI-driven solution capable of analyzing
personal wardrobes and delivering intelligent style recommendations. Clients needed an efficient way
to discover optimal outfit combinations, particularly for special occasions, inspired by their chosen
celebrity’s style while aligning with their own wardrobe and preferences.
Key challenges faced by the organization.
Limited Technological Integration in Fashion: The industry lacked AI-powered tools
that could enhance user experience by providing interactive and data-driven fashion recommendations.
Lack of AI-Driven Personal Styling: No existing system could analyze a user’s
personal wardrobe and provide tailored fashion recommendations.
Difficulty in Finding Optimal Outfit Combinations: Clients struggled to efficiently select the
best outfit combinations, particularly for special occasions.
Bridging Celebrity Style with Personal Wardrobes: The industry lacked AI-powered tools
that could enhance user experience by providing interactive and data-driven fashion recommendations.
Enhancing Customer Engagement: The organization sought to differentiate itself by leveraging
AI-driven solutions to attract and retain clients through personalized styling experiences.
Solution
To address these challenges, Softcodeit Solutions partnered with this organization to develop an AI-powered
fashion assistant that digitizes wardrobes, provides celebrity-inspired style guidance, and offers personalized
outfit recommendations through a virtual AI stylist. The key features of this solution include,
AI-Powered Wardrobe Digitization: The system enables users to catalog their entire wardrobe
effortlessly by scanning their clothing items through a video onboarding process, eliminating the need for
manual data entry. Integrated Gemini video API and vector-based data storage ensure efficient processing of
wardrobe data, enabling accurate fashion recommendations.
Intelligent Style Recommendations: Leveraging AI and natural language processing (NLP),
the platform analyzes wardrobe data to suggest the best outfit combinations for various occasions, enhancing
personal styling choices.
Celebrity-Inspired Fashion Guidance: Users can select a celebrity, and the system provides
tailored outfit recommendations based on their existing wardrobe, bridging the gap between inspiration and
practical application.
Interactive AI Chat Stylist: Instructors could provide valuable e-books to students, enabling them to download
and access specific sections directly linked to their lessons.
The platform was developed using Next.js and React for the frontend, with a Python Flask backend, ensuring a
responsive and robust architecture. It leverages Large Language Models (LLMs) from ChatGPT, Gemini, and Anthropic
to power AI-driven features such as video-based wardrobe digitization, personalized style analysis, and an
interactive AI Chat Stylist. To enhance precision and efficiency, the system integrates custom Named Entity
Recognition (NER) for attribute extraction, along with advanced prompt engineering and templating to optimize
LLM outputs. It utilizes vectorization (text-embedding-ada-002) and Qdrant for efficient wardrobe data management,
while MongoDB serves as the primary database for application data storage.
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