Culture is currently the gold standard for diagnosis of urinary tract infections (UTIs); however, it has poor sensitivity detecting urogenital pathogens, especially if patients have already initiated antimicrobial therapy, or have an infection from an organism that is not commonly cultured. False negative urine culture results can lead to the inappropriate use of antimicrobial therapies or to the progression to urosepsis in high-risk patients. Though not commonly applied to urine in a clinical setting, Next-generation sequencing (NGS)-based metagenomics offer a solution as a precision diagnostic. We developed and validated BIOTIA-ID, a clinical-grade NGS-based diagnostic pipeline for the detection and identification of pathogens in urine specimens. Remnant clinical urine specimens, and contrived sterile urine spiked with common UTI pathogens, were processed with our end-to-end assay including extraction, metagenomic library preparation and Illumina NextSeq 550 sequencing. We trained and applied a bioinformatic pipeline that uses machine learning (ML) to identify pathogens. Internal controls and other quality control measures were incorporated into the process to provide rigorous and standardized results. The assay was tested on 1,470 urine specimens and achieved 99.92% sensitivity, 99.95% specificity and a limit of detection (LoD) of <25,000 CFU/mL and <5,000 CFU/mL in bacteria and fungi, respectively. Discordant results were reconciled with additional testing by target-specific qPCR or 16S Sanger sequencing; 87% of the NGS results were ultimately determined to be the correct result. Overall, these data demonstrate that BIOTIA-ID is a highly accurate clinical-grade diagnostic tool with notable advantages over current culture-based diagnostics