Foot deformities are a common yet often overlooked health issue that can lead to chronic pain, impaired mobility, and a reduced quality of life. These deformities, which may be congenital or acquired, can significantly affect gait and posture, leading to further complications in the knees, hips, and spine over time. Individuals with chronic conditions like diabetes are particularly at risk, as even subtle deformities can exacerbate their symptoms and complicate care. Early and accurate diagnosis is crucial to prevent long-term issues, yet many foot deformities go unnoticed by both patients and general practitioners. The SMART Foot ( A Scalable Machine Learning Algorithm for Real Time Diagnosis of Foot Deformities) Project, funded by the ICMR, is a pioneering initiative of the FABER laboratory aimed at developing a scalable machine learning algorithm for the real-time diagnosis and classification of foot deformities. Targeting a common issue that often goes undiagnosed, this project seeks to create an annotated image database and train several AI models to accurately identify foot deformities from pictures of feet. Once complete, this tool could transform foot deformity diagnosis by providing a quick, accessible, and reliable solution, potentially as a web or mobile app, to aid clinicians in early and accurate identification of foot deformities.