This study investigates the impact and mechanisms of Rasayana Churna, an Ayurvedic poly-herbal formulation, in treating aging-related disorders through text mining, network pharmacology, molecular docking simulation, Super-MMPBSA, and density functional theory. The text mining of Rasayana Churna highlighted the diverse therapeutic potential of Phyllanthus emblica, Tinospora cordifolia, and Tribulus terrestris in managing aging-related disorders through their antidiabetic, antioxidant, and anti-inflammatory properties. Using network pharmacology, 17 bioactive compounds and 137 corresponding potential targets of Rasayana Churna were identified and used to construct protein–protein interaction and hub gene networks. Key targets such as AKT1, BCL2, ESR1, and GSK3B were linked to aging-related pathways, with GO and KEGG enrichment analyses highlighting processes like apoptosis, oxidative stress response, and pathways like PI3K-Akt signaling. Molecular docking analysis identified 14 compounds with strong binding affinity toward the key aging target AKT1. Three bioactive compounds—Kaempferol, N-Caffeoyltyramine, and Multifidol glucoside—exhibited superior stability and binding interactions in MD simulations, confirmed by RMSD, RMSF, Rg, hydrogen bonding, SASA, PCA, and free energy landscape analysis. Super-MMPBSA (last 30 ns) calculation was performed to analyze dynamic behavior and protein–ligand stability, revealing significantly lower ΔG binding free energy values for the three hit compounds (− 177.871, − 164.855, − 199.649 kJ/mol, respectively) compared to the AKT1-reference complex (− 109.463 kJ/mol). DFT analysis revealed favorable electronic properties and kinetic stability for these compounds. Integrating traditional Ayurvedic knowledge with computational techniques suggests Rasayana Churna could prevent and manage aging-related conditions. However, further in vitro, in vivo, and clinical studies are needed to validate its aging-modulatory potential.