One of our clients, a mid-sized business managing hundreds of vendor relationships, was struggling with a growing volume of incoming invoices—usually hundreds per day. Each invoice had to be manually reviewed, with important details like invoice number, vendor name, line items, and payment terms keyed into their ERP system. The process was not only time-consuming, but also prone to human error. This created a serious bottleneck in their accounts payable workflow, delayed reporting, and occasionally led to missed payment deadlines or duplicate entries.
To address this, we implemented an AI-powered invoice processing solution using Nanonets. We began by training the system on the specific invoice formats used by their vendors—some of which followed inconsistent or non-standard layouts. Using machine learning, the AI was able to quickly learn how to identify and extract the relevant fields from each document, even when layouts varied. The solution was integrated directly with the client’s ERP system, allowing extracted data to flow seamlessly into the correct fields without any manual intervention.
Since deployment, the results have been transformative. The client has eliminated virtually all manual data entry related to invoice processing. Invoices are now scanned or forwarded to a central inbox, automatically processed, and logged into the ERP system within minutes. The accuracy of data extraction has increased dramatically, freeing up their accounting team to focus on higher-value tasks like reconciliation and vendor management. What was once a daily headache has become a streamlined, reliable, and scalable part of their operations.