Despite major technological advancements, cardiovascular diseases remain the leading cause of death in the modern world, creating an urge for rapid, accurate, and low-cost diagnostic systems. The paper proposes an AI-enabled cardiovascular risk assessment platform that supports clinicians in early detection and risk evaluation by considering real-time image processing and smart analytics. This system interprets angiography images automatically by means of advanced computer vision techniques like Otsu thresholding and Gaussian filtering, which help to identify blood vessels and calculate stenosis percentages with accuracy greater than 95%. Further, a multi-factorial risk-scoring algorithm is used to combine imaging data with medical history and lifestyle information in generating a personalized health profile. It provides a comprehensive diagnostic report consisting of adaptive health recommendations that can be downloaded or shared with healthcare providers. In contrast to traditional methods, requiring manual image analysis for 24–48 h, the proposed solution gives instant, low-cost, highly accurate results on any device, reflecting a significant development toward intelligent, real-time cardiovascular care.