<p>The multifactorial neurodegenerative disease known as Alzheimer’s disease (AD) is typified by amyloid-β aggregation, tau hyperphosphorylation, neuroinflammation, and synaptic dysfunction, as well as progressive cognitive decline. Due to the limited effectiveness of conventional therapeutic approaches, multi-target agents must be investigated. A traditional Ayurvedic polyherbal formulation, Triphala contains a wide range of bioactive phytochemicals that have been shown to have neuroprotective effects. The molecular targets of Triphala phytocompounds related to AD pathology were clarified in the current study using a network pharmacology approach. BindingDB and SwissTargetPrediction were used to predict the putative protein targets of 18 phytocompounds, yielding 54 distinct targets. The STRING database was used to build a protein–protein interaction (PPI) network, which Cytoscape was then used to analyse. The following 7 important hub genes were identified using topological parameters (degree, betweenness, closeness centrality): BCL2, CASP3, MMP9, JUN, NFKB1, PTGS2, and ESR1. Potential mechanistic overlap was highlighted by the significant involvement of 20 genes in AD-related pathways and 30 genes in the lipid and atherosclerosis pathway, according to gene enrichment analysis using KEGG. Synaptic plasticity, oxidative stress response, neuroinflammatory signalling, and apoptosis regulation are the main functions of these genes. The integrative analysis highlights Triphala’s polypharmacology mechanism and raises the possibility that it could be used as a multi-target therapeutic candidate for AD. This study offers a logical foundation for additional in vitro and in vivo validation of Triphala-derived neurotherapeutics as well as a systems-level framework for comprehending herb-compound-gene-disease interactions.</p> Graphical Abstract <p></p>