ଭାଉଚିଂ means matching every booked ଲେଣଦେଣ to its underlying ଚାଲାନ୍ or supporting document. The traditional approach is three articles, six ଘଣ୍ଟା, a thousand ଭାଉଚର୍. CORAA's ଭାଉଚିଂ agent uses OCR to extract amount, date, ଭେଣ୍ଡର୍ GSTIN, ଚାଲାନ୍ number, and TDS deducted from uploaded PDFs and images. The extracted data matches against the ଲେଜର୍ entry; mismatches above tolerance get flagged with the source image attached.
Two paths to the same audit conclusion. One leaves traces; the other doesn't.
Bulk upload PDFs and images. CORAA accepts ZIP archives, folder uploads, or drag-and-drop. Files can come from the client's email, scanned cabinet, or accounting system attachments.
OCR reads every page. Extracted fields: amount, ଚାଲାନ୍ number, date, ଭେଣ୍ଡର୍ GSTIN, ଭେଣ୍ଡର୍ name, TDS deducted, GST split (CGST / SGST / IGST). The extracted data matches against the GL on amount + party + date within configurable tolerances.
Mismatches surface in the ଭାଉଚିଂ ୱାର୍କିଂ ପେପର୍. Each row shows the source image, the OCR extraction, the matched ଲେଜର୍ entry, and the variance. The ଅଡିଟର୍ accepts the match, flags for client clarification, or rejects.
Trained on Indian ଚାଲାନ୍ formats: GST ଚାଲାନ୍, Bill of Supply, debit notes, credit notes. Extracts the standard 7-8 fields per ଚାଲାନ୍ with high accuracy.
Invoice amount, ଲେଜର୍ entry amount, and PO amount (if Bill register loaded) matched three ways. Variances surface at any leg.
For every ଲେଜର୍ entry without a matched ଚାଲାନ୍ in the upload set, CORAA lists it as missing-support. The ଅଡିଟର୍ sends this list to the client through Client Portal as a single questionnaire.
Every ଭାଉଚର୍ carries its match history: who uploaded the ଚାଲାନ୍, when OCR ran, what was extracted, who accepted the match, who flagged it. Preserved per SA 230.
