HeyFriend Helper: A Conversational AI Web-App for Resource Access Among Low-Income Chicago Residents
Maddie Juarez, Abha Rai, Kristen E. Ravi, Margaret C. Delaney, Danny Olweean, Eric Klingensmith, Swarnali Banerjee, Neil Klingensmith, George K. Thiruvathukal

TL;DR
HeyFriend Helper is a web-based conversational AI platform designed to assist low-income Chicago residents with employment resources, digital literacy, and well-being support through an integrated, personalized interface.
Contribution
This work introduces a comprehensive conversational AI system that combines multiple local resources to support low-income individuals' employment and well-being needs.
Findings
Career-readiness tools and CUIs are effective in providing holistic support.
The platform successfully integrates resume feedback, interview practice, and community resources.
Interdisciplinary collaboration enhances resource accessibility for underserved populations.
Abstract
Low-income individuals can face multiple challenges in their ability to seek employment. Barriers to employment often include limited access to digital literacy resources, training, interview preparation and resume feedback. Prior work has largely focused on targeted social service or healthcare applications that address needs individually, with little emphasis on conversational AI-driven systems that integrate multiple localized digital resources to provide comprehensive support. This work presents HeyFriend Helper, a web-based platform designed to support low-income residents in Chicago through an interactive conversational assistant that provides personalized support and guidance. HeyFriend Helper integrates multiple tools, including resume building and feedback, interview practice, mindfulness and well-being resources, employment trend and career outcome information, language…
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