Metabolomics is considered a potential technique for clinical diagnosis, molecular medicine, therapeutic drug monitoring, and drug development. The conventional metabolomics analysis pipeline depends on IDA technique. Although it is a powerful technique, it is still suffering from stochastic, not reproducible ion selection across samples. Furthermore, even though the presence of different workbenches for metabolomics, metabolites identification remains a tedious task and time-consuming. Consequently, SWATH acquisition has attracted much attention to overcome this limitation. Therefore, a novel SWATH platform for data analysis had been developed with a generation of an accurate mass spectral library for metabolite identification using SWATH mass spectrometry acquisition that relies on the alignment of transition ions. The workflow was validated using standards inclusion/ exclusion compounds list. The false-positive identification was 3.4% from the non-endogenous drugs and the false negative was 10% of the standards with 90% sensitivity and 96.6% specificity. Ions with height ratio samples to blank ≥ 5, ABS retention time shift for each fragment < 0.1417%, ABS peak width at half height for each fragment in relation to precursor ion <17.4965 were kept. The workflow has the availability to subtract the background noise although the complexity of the SWATH sample. Besides, the reality of the identified transition. To demonstrate the feasibility of the workflow strategy, 1282 compounds from HMDB were tested in a variety of biological samples. In the current study, 377 compounds in positive mode and 303 in negative one with 392 unique non-redundant metabolites were recorded. After workflow validation, a free software tool, termed SASA, was developed to analyze SWATH acquired samples.