A comprehensive proteome map is essential to elucidate molecular pathways and protein functions. Although great improvements in sample preparation, instrumentation and data analysis already yield-ed impressive results, current studies suffer from a limited proteomic depth and dynamic range there-fore lacking low abundant or highly hydrophobic proteins. Here, we combine and benchmark advanced micro pillar array columns (µPAC) operated at nanoflow with wide window acquisition (WWA) and the AI-based CHIMERYS search engine for data analysis to maximize chromatographic separation power, sensitivity and proteome coverage. The wide window acquisition method merges the strengths of DDA and DIA. WWA uses a broad isolation window (≥4 Th) for data-dependent precursor selection. Similar to DIA, precursor ions close to those selected are co-fragmented, producing chimeric spectra that boost IDs and improve coverage of low-abundance peptides, which would otherwise be missed. WWA is particularly powerful when combined with the AI-driven CHIMERYS search algorithm, which allows confident identification of up to eleven peptides from a single chimeric spectrum. Developed by MSAID, the CHIMERYS algorithm makes use of accurate fragment spectrum predictions trained on millions of spectra, which allows to utilize additional spectral properties such as relative signal intensities for drastically improved identification rates. Entrapment experiments were conducted searching mouse immunoprecipitation samples with MS Amanda 2.0 and CHIMERYS by applying an additional custom-made decoy database, which demonstrated excellent protein, peptide and PSM FDR control from 1% upwards for both search engines. Combining wide precursor isolation widths of 4-12 Th with the CHIMERYS search engine identified 51-74% more proteins and 59-150% more peptides for single cell, immunoprecipitation and multi-species samples in comparison to a standard proteomics workflow employing MS Amanda 2.0 and an isolation width of 1 Th. Application of different isolation widths revealed that the optimal isolation window size varies according to sample amount and complexity with 12 Th resulting in the highest number of identifications for single cell-equivalent injection amounts, while 4 Th provided best results for classical bulk inputs of 400ng. Evaluation of coefficients of variation also yielded improved results for WWA over classical DDA when assessing single cell, 40 cell and 250pg bulk HeLa lysates. Overall, WWA and CHIMERYS resulted in substantially improved proteomic depth and quantification for all sample types tested and will provide a highly valuable toolset for the proteomics community.