A Hyderabad-based startup, Swaasa, has introduced an innovative smartphone-based respiratory sound diagnosis tool to detect potential tuberculosis (TB) cases in East Godavari district, Andhra Pradesh, India. This pilot initiative, part of the MedTech Innovation Challenge 2025, has successfully screened approximately 8,000 individuals, revealing that nearly 36% of identified TB cases were asymptomatic, which traditional screening methods might have missed. The AI-powered platform analyzes cough sounds recorded via smartphones, allowing healthcare workers to conduct door-to-door screenings efficiently. The initiative has reportedly improved TB diagnostic yield by around 15% compared to conventional Active Case Finding methods. Additionally, the screening uncovered a hidden burden of chronic respiratory illnesses among villagers, with chronic obstructive pulmonary disease (COPD) risk ranging between 6.5% and 9.5% and asthma risk between 1.6% and 1.9%. The platform's non-invasive nature and integration with national health systems make it a promising model for large-scale deployment in public health initiatives. Swaasa plans to expand its AI-enabled screening model across multiple districts in Andhra Pradesh, aiming to enhance the effectiveness of TB detection and treatment in rural communities.