Ayurvedic medicine offers a holistic approach to managing complex diseases such as Type 2 diabetes mellitus, which is primarily driven by insulin resistance. Bioinformatics has emerged as a powerful tool for understanding the molecular mechanisms underlying the effects of Ayurvedic drugs on insulin resistance pathway targets. This study uses bioinformatics techniques to analyze the pharmacological potential of Ayurvedic herbs traditionally used to treat diabetes, such as Gymnema sylvestre and Withania somnifera. The key bioactive compound in G. sylvestre has been shown to suppress the taste of sugar and reduce glucose absorption in the intestines, promoting better blood sugar control. Also, recent studies highlight W. somnifera role in improving insulin sensitivity and reducing blood sugar levels Using databases like DrugBank, STITCH, and PubChem, active compounds in these herbs were identified, and their interactions with key targets in the insulin signaling pathway, including IRS1, PI3K, and GLUT4, were analyzed. Molecular docking, network pharmacology, and gene expression analyses revealed that these phytochemicals potentially modulate glucose uptake, insulin sensitivity, and inflammation, key processes involved in insulin resistance. Our findings suggest that the synergistic effects of these herbs could offer a complementary approach to managing insulin resistance, warranting further experimental validation. The study paves the way for rational drug design based on traditional knowledge. It contributes to the growing field of systems biology in exploring the efficacy of multi-compound, multi-target therapeutic strategies.