AI-based source-to-pay solution provider, Aavenir, has revealed the recent version of Invoiceflow, which makes invoice processing more comprehensive for a wide range of purposes. Automatic invoice extraction, categorization, and digitization for the accounts payable process can be done using artificial intelligence (AI) through Invoiceflow. Invoice formats of different kinds can be managed using machine learning algorithms developed over time. Before being routed through ServiceNow’s Now Platform’s dynamic approval workflow, the solution compares invoices against POs, invoices, agreements, and vendor details.
Jesal Mehta, CEO of Aavenir stated that “Aavenir involves customers in its product development, therefore all solutions are designed for customers and by customers. The new version of Invoiceflow processes most invoices without intervention, eliminating 80% to 90% of manual effort and offers up to 99.5% accuracy.” Invoiceflow integrations provide the single version of truth for project management, finance, and procurement teams across applications,”
The Invoiceflow AI engine now includes industry-leading data extraction accuracy, discount extraction, multiple invoices collecting from a single document, and simpler invoice field mapping. Expanding 2/3-way invoice data matching allows for the detection of duplicate or incorrect invoices. ServiceNow solutions such as PPM and ITBM will be able to fully integrate with systems such as SAP and Salesforce.
The addition of multi-language support, customizable views, drag-and-drop service, and other features improves the customer experience. Workflows are more adaptable, and approvals are executed more quickly using dynamic delegation of approval power. The latest update enables approvers to view PO/vendor details, audit history, and duplicate status, as well as easily approve or reject bills from the invoice list/email. Using role-based dashboards for AP performance analysis, users can view invoice status, generate metrics reports, and optimize the workload. The use report may be used to measure AP staff productivity and identify potential problems.
