A leading retail company’s Accounts Payable team processed invoices in hundreds of different formats, manually extracting data from each one to enter into their ERP system. The sheer variability made standard automation approaches expensive to maintain, since formats kept changing.
On top of that, manual entries into the “Goods Received” register added another layer of complexity and another point where delays and errors could creep in.
• High variability across hundreds of invoice formats
• Manual, repetitive data extraction into the ERP system
• High TAT from the sheer volume of manual handling
• Seasonal spikes in invoice volume straining the team further
• Errors and duplicate payments slipping through manual checks
Aiwozo combined OCR with a continuously learning AI model to handle invoice variability at scale, backed by DocuBot for ERP entry.
Capture agents used OCR to convert invoice documents regardless of format into digitized text.
Extraction agents, powered by an AI/ML model, pulled the relevant data from each invoice. The model was trained on both historical and real time data, so accuracy kept improving over time rather than staying fixed.
Exception handling routed any invoice the model couldn’t confidently process to a human reviewer and the correction was fed back into the model, continuously sharpening its accuracy on the formats it saw next.
DocuBot then took the verified, extracted data and entered it directly into the ERP system, completing invoice processing without manual re-entry.
See Aiwozo DocuBot in action:
Key business and operational challenges that limited performance, scalability, and governance before automation was introduced.
