MirakiTech

MirakiTech / Success Stories / PRISMA APP

Next-Gen LMS Boosted UPSC Success Rates, Positioned the Institute as a Leader

The Client:

PRISMA

Industry:

Fashion & Lifestyle, Retail

Objective:

To elevate customer engagement through immersive AI-driven fashion experiences and streamline outfit visualization using customer inputs.

Solution Offered:

Custom AI-Powered PRISMA Application featuring an interactive fashion chatbot

Client in Spotlight

One of the most recognized fashion brands sought to redefine how customers interact with their collections online. They envisioned a solution that could personalize the shopping experience, allowing users to visualize outfits on models generated from simple prompts or uploaded clothing items. MirakiTech partnered with the brand to create an innovative AI-powered PRISMA application, designed to bridge fashion and technology seamlessly.

Major Challenges

  • Unstructured Image Data Handling: Difficulty interpreting and using diverse garment images submitted by users
  • Customer Experience Gap: Limited interactivity and visualization options in existing digital channels
  • Personalization Needs: Lack of AI-based fashion assistants for styling recommendations and outfit previews
  • Manual Design Input: Time-consuming garment fit and visualization processes
  • Scalability Issues: Inability to scale interactive experiences across multiple devices and use cases

Solving the MirakiTech Way

Approach

We worked closely with the brand’s product and digital teams to design a fashion chatbot powered by the OOTDdiffusion LLM model, fine-tuned for garment styling. The AI chatbot accepts any input garment, styles it on an AI-generated model, and allows users to customize the background—all through simple prompts.

Process

The journey began with rapid prototyping and model fine-tuning to ensure high image fidelity and realistic overlays. Python scripting powered the backend intelligence, while Streamlit was used to develop an intuitive frontend. Rigorous testing was conducted to validate prompt interpretation, garment fitting, and customization flows before a successful multi-device rollout.

Tech Stack

Python

Streamlit

OOTDdiffusion (LLM model)

Custom AI image processing modules

Key Functionalities of the e-commerce App Included

  • Garment input and overlay on AI-generated model
  • Prompt-based model generation
  • Background customization using natural language prompts
  • Image-based garment recognition and fit estimation
  • Real-time visualization for styling feedback

The Transformative Outcomes

  • The AI-powered tool enabled users to visualize their outfits on personalized AI models, enhancing user engagement and decision confidence.
  • Real-time garment overlays and model rendering reduced dependency on manual design trials.
  • Background customization through simple prompts brought a new level of immersion to fashion exploration.
  • Customer experience saw a significant uplift with dynamic, on-demand outfit styling.
  • The application scaled across campaigns and seasons, allowing for broader usage and customer adoption.
  • The fashion brand positioned itself as a tech-forward innovator, setting new standards in digital shopping experiences

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