Raman spectroscopy combined with artificial intelligence offers a groundbreaking approach to early cancer diagnosis. This technology analyzes surface-enhanced Raman Scattering (SERS) of plasma metabolite profiles or exfoliated cells, which change with cancer progression. Artificial Intelligence (AI) -based classification of these SERS fingerprints enables sensitive and non-invasive cancer detection and staging. The method's non-invasive nature and minimal sample preparation requirements make it highly practical for clinical diagnosis. This innovative approach can potentially revolutionize cancer management by promoting earlier and more precise treatment interventions. Importantly, the technology can detect asymptomatic cancers, potentially leading to improved survival rates through early intervention. Additionally, its cost-effectiveness and ability to provide digital pathology findings make it a promising tool for widespread implementation in various healthcare settings, including resource-limited areas.