MenoEaze: An Empathetic Retrieval-Augmented Generation Companion for Menopause Management

Menopause is a profound biological and psychological transition for women, and yet it is markedly under-served in the digital health sector, represented largely by limited, non-empathetic, and non-evidence-based digital support. Most existing solutions focus on passive data tracking without personalized empathetic guidance. It creates a clinical trust deficit and increases emotional isolation. This paper introduces MenoEaze, an AI-powered conversational avatar grounded in a state-of-the-art Retrieval-Augmented Generation architecture coupled with an advanced set of empathic design principles. The core functionality of the system is to provide highly individualized, evidence-based nutritional and emotional support for midlife women affected by menopausal symptoms. Anchoring responses in a curated knowledge base of authoritative medical sources, the RAG architecture suppresses the critical issues of hallucination and inconsistency of generalized LLMs. MenoEaze will be designed as a modular approach so that contextual and emotional awareness can be achieved to address the important ethical challenges regarding bias, interpretability, and the critical requirement for perceived authenticity in human-AI interaction. This will include rigorous multi- stage evaluation against the S.C.O.R.E. framework- Safety, Consensus, Objectivity, Reproducibility, and Explainability for the developed system to ensure clinical accuracy and trustworthiness superior to the generic chatbots. MenoEaze aims at transforming menopause care into a proactive, supportive emotionally intelligent experience from being a reactive, data-centric service.