A smart OCR + extraction system that turns messy, multi‑format statements into clean, structured data—ready to load.
This is the story of an audit firm with many clients and even more documents. Invoices, vouchers, receipts, activity reports—each arriving in its own style, each speaking a slightly different language. The team stored the files neatly, but the numbers inside still had to be typed by hand into Excel, lined up to a strict template, and then uploaded in batches. Hours slipped away. Small mistakes crept in—an extra zero here, a wrong date there. Auditors waited for clean data before they could begin real analysis. The work felt like copying signs from a busy street into a notebook, careful but slow.
This is the story of an audit firm with many clients and even more documents. Invoices, vouchers, receipts, activity reports—each arriving in its own style, each speaking a slightly different language. The team stored the files neatly, but the numbers inside still had to be typed by hand into Excel, lined up to a strict template, and then uploaded in batches. Hours slipped away. Small mistakes crept in—an extra zero here, a wrong date there. Auditors waited for clean data before they could begin real analysis. The work felt like copying signs from a busy street into a notebook, careful but slow.
Accept multiple document formats (PDFs, scans, images, XLSX). Extract the correct financial fields despite layout differences. Provide confidence scores and quick review to preserve accuracy. Transform fields into the firm’s canonical structure. Auto‑submit to the existing system with audit logs and error handling. Keep data secure and compliant (PII, financial records).
Apptriangle Limited introduced an AI Document Processing system built for audit rhythms. In practice, it felt natural: staff upload the statements to the web app; the AI builder recognizes the document type and reads it like a sharp‑eyed clerk, pulling out the right fields—supplier, date, invoice or voucher number, line items, amounts, taxes, currencies, totals—and mapping them into the firm’s standard shape, no matter how the original looked. Each extraction comes with confidence markers, like quiet traffic lights on the fields that need a second glance; reviewers tap once, fix a detail, and move on. With Submit, the system sends the structured data to the firm’s existing platform via API or export, attaches the source file, and writes a full audit trail—who uploaded, when, and what changed.
When piles of documents arrive, batch mode turns into a steady conveyor, handling hundreds at once. Exception rules raise clear flags—for example, when the total doesn’t match the sum of lines—so problems are seen before posting, not after. The effect is simple and strong: typing errors fade, cycle time collapses, and auditors receive clean, consistent data far sooner. The craft of auditing remains; the way of feeding the numbers becomes calm, accurate, and fast. From retyping to capturing, from waiting to working—the firm finds a pace it can trust.
