AIMM develops smartphone-based AI tools for low-cost, real-time child nutrition monitoring. The project uses image-based artificial intelligence, including RGB and infrared imaging, to estimate key anthropometric indicators such as MUAC, height, weight, and weight-for-height risk categories without relying on physical scales or measuring tapes. Implemented in Maharashtra, India, AIMM is designed to support early detection of undernutrition among children aged 6–59 months, particularly in rural and underserved settings where conventional nutrition surveys are costly, infrequent, and difficult to sustain. The app is being developed with a strong focus on usability, privacy, and household-level adoption, enabling caregivers to monitor children’s nutritional status directly while supporting community-level early warning and data-driven policy decisions. AIMM builds on previous work in predictive nutrition monitoring and advances it by transforming the data collection process itself: from periodic, expert-led measurement to accessible, AI-assisted monitoring that can be used closer to the household.