The increasing generation of agro-industrial byproducts, such as spent brewer’s grain (SBG) and soybean processing residues (e.g., okara or soy waste), presents both an environmental challenge and an untapped opportunity for sustainable biomanufacturing. These biomass wastes are rich in proteins, peptides, dietary fiber, and bioactive precursors, yet they are often underutilized or disposed of as low-value feed or waste. Converting such residues into high-value functional peptides offers a promising strategy to support circular bioeconomy and sustainable food innovation. This project aims to develop an integrated biomass upcycling platform for the production of functional peptides from protein-rich agro-industrial residues. Through enzymatic hydrolysis, fermentation, and peptide fractionation, valuable peptide mixtures with targeted bioactivities—such as antioxidant, anti-inflammatory, antihypertensive, antimicrobial, or metabolic health-promoting properties—can be generated. To accelerate discovery and improve process efficiency, artificial intelligence (AI) and machine learning (ML) will be incorporated to predict peptide bioactivity, optimize hydrolysis/fermentation conditions, and identify sequence–function relationships from complex peptide datasets. By combining green bioprocessing with AI-assisted functional peptide discovery, this project seeks to transform low-value biomass waste into next-generation nutraceutical, food, feed, or cosmetic ingredients. The proposed work not only advances sustainable valorization of agro-industrial residues but also establishes a data-driven platform for future precision biorefinery applications.