Invoice PO Matching
Matching a PO involves numerous processes, such as receiving and capturing invoice data, cross-referencing it with the purchase order, matching the parameters, and resolving the issue based on the parameters.
When handled manually, Invoice PO matching is an expensive and time-consuming function for your organization. Inputting inaccurate data from an invoice can be very costly; these inaccuracies can result in overpayments and wasted employee hours spent resolving issues with vendors.
Most common issues during Invoice-PO matching:
About AIBridge ML:
AIBridge ML, a sister company of Ray Business Technologies, offers cutting-edge services to its customers around AI, Deep Learning, and RPA. Collaboratively deliver enterprise Data Science, WCM, DXP, ERP, CRM, and integration solutions worldwide.
AiMunshi is a powerful Document Processing and Invoice Automation Platform that enables seamless collection, processing and transfer of data across file systems and documents.
Powered with Artificial Intelligence, it offers smart capturing features and can store critical data available in different formats including Image Capturing and hand-written notes, and made readily available for external networks with authorized access.