This repository contains my independent research study on identifying compatibility gaps in 10-minute home-help platforms such as Pronto and Snabbit.
The research analyzes existing matching systems, identifies critical userβhousehelp compatibility issues, and proposes an AI-driven framework to improve service quality, transparency, and user experience.
- Conducted a 17-page independent research study.
- Identified six major compatibility mismatch categories.
- Proposed a Dual-Profile Compatibility Matching Framework.
- Designed an AI-powered multilingual voice onboarding system for digitally underserved househelps.
- Developed an end-to-end compatibility-aware booking workflow.
- User Experience (UX) Research
- Human-Centered Design
- Artificial Intelligence
- Workflow Analysis
- Product Design
- Service Optimization
The complete research paper is available in this repository.
File: research_study.pdf
Rishita Rathi
B.Tech β Artificial Intelligence & Data Science
Thakur College of Engineering and Technology
π§ itsrishitarathi345@gmail.com
π LinkedIn: https://www.linkedin.com/in/rishita-rathi-530ab42b1