Vitamins are essential for our overall health. A deficiency in vitamins can lead to various health issues. To combat this issue, we have developed an AI system that can diagnose vitamin deficiency at an early stage. The proposed technique is a web-based free application. Concerned only on the identification of vitamin deficiencies which our any requirement of manual blood sample tests. In place of blood samples, the human gives the input as eye images which are analyzed using the advancements in machine learning techniques that are trained on taken datasets. These examinations provide the suggestions of vitamin rich foods and dietary and time recommendation according to intake of food. Pregnancy times are very hard to women’s where they need rich nutritious food and intake must be well nutritional. These techniques play a vital role in emergency conditions of pregnancy women in the time of delivery and well-being of baby. This approach helps mitigate risks of health issues such as anemia, pregnancy-related complications, and increased susceptibility to infectious diseases. In today’s fast-paced environment, ensuring a diet rich in essential vitamins is vital for maintaining health and well-being. However, vitamin deficiencies often go undiagnosed until they lead to severe health problems. Among various detection methods, advanced technology presents an effective solution for early diagnosis and intervention. This research investigates a method for detecting vitamin deficiencies through eye image analysis. The human eye, with its intricate network of blood vessels and tissues, offers significant insights into an individual’s nutritional health. Through the use of advanced image processing techniques and specialized algorithms, this study aims to detect signs of vitamin deficiencies, empowering individuals and healthcare providers to make timely, informed decisions for better health outcomes.