Individuals with unmet health-related social needs (HRSNs), including housing, food, and/ or financial instability, are twice as likely to suffer from physical health problems and children are three times more likely to experience cognitive developmental delays. These challenges underscore the need for early and efficient identification and intervention; however, current methods for identifying specific needs and referring individuals to the appropriate resources present their own obstacle as they often require time- and resource-intensive in-person interactions. Thus, there is a growing need to a scalable and efficient service to streamline assessments and improve care. Here, the inventors propose an AI-driven, open access conversational agent (chatbot) identify HRSNs in a resource-limited setting. Importantly, this technology would improve access in populations with limited connectivity as it is designed to operate offline on standard devices (i.e. smartphones, tablets) and includes a privacy-first model in which interactions remain locally stored and encrypted to reduce risk of data breaches of this sensitive health information. This chatbot is intended for use in primary care/ pediatric clinics for real-time HRSN screenings and referrals, community health and outreach organizations, and public health agencies, but could be further adapted for applications in mental health triage, crisis intervention, and chronic disease management. Currently, this technology is a proof-of-concept prototype with AI-driven synthetic data generation; however, will soon advance to a pilot study to evaluate chatbot accuracy and usability.