Thermo Fisher Scientific and MSAID have collaborated to provide proteomics researchers with advanced mass spectrometry software that generates market-leading biological insight from acquired data by substantially increasing peptide identification and quantitation capabilities using artificial intelligence and deep learning. Thermo Scientific Proteome Discoverer 3.0 software with CHIMERYS by MSAID leverages artificial intelligence to substantially enhance the identification rate and number of unique peptide identifications in proteomics data. CHIMERYS identifies a minimal set of peptides that can explain the acquired tandem mass spectrum, in comparison to existing methodologies, which typically assume all peaks in a tandem mass spectrum are derived from a single peptide. This innovative approach provides a 1.8-fold increase in the number of unique peptide identifications and a 1.5-fold increase in the number of protein identifications for typical proteomics data sets when compared to existing tools. In addition to improved protein coverage and quantitation capabilities, Proteome Discoverer 3.0 software paired with CHIMERYS also facilitates faster data acquisition for increased sample throughput. Thermo Fisher Scientific and MSAID are showcasing their new software solution during the 69th American Society for Mass Spectrometry Conference on Mass Spectrometry and Allied Topics, being held October 31-November 4, in the Pennsylvania Convention Center, Philadelphia, Pennsylvania. The Proteome Discoverer 3.0 software release also includes an updated INFERYS prediction model, extending support to tandem mass tagging, collisionally induced dissociation, and providing improved results for immunopeptidomics. By pairing intelligent data analysis through Proteome Discoverer 3.0 software and CHIMERYS with leading hardware technology in the Thermo Scientific Vanquish Neo Ultra-High Performance Liquid Chromatography system and Thermo Scientific Orbitrap mass spectrometry platforms, researchers will be empowered to continue pushing the boundaries of proteomics research.