Skin and soft tissue infections (SSTIs) are one of the most common infections in India affecting 10-12% of Indian population. They are caused by a variety of bacteria and fungus, which makes it harder to diagnose and propose an effective treatment immediately especially in low resource settings due to the lack of access to qualified physicians. Management of SSTIs requires early expert infection assessment and remains a major challenge for the clinicians. A hand-held device is developed leveraging the inherent autofluorescence properties of the bacterial and fungal species that can non-invasively and rapidly identify the pathogens on SSTI using multispectral imaging followed by image processing and machine learning algorithms. The device is able to classify the gram type with < 85% accuracy.