PO (Purchase Order) invoice processing is a recurring use case within an organization. With increasing business, the demand for processing more POs per day is also increasing, let’s see how AI can help with this.
Producing purchase orders are essential to any company. They provide an overall understanding of the assets a company is buying, playing a vital role in the company’s economic decisions. This helps a company strategize more optimized processes to ease out the acquiring cost of services and materials.
Yet, there are certain challenges that are associated with purchase order invoice processing. This is for the same reason, we have written this article to give you a basic understanding about POs, the process associated, challenges, and how AI can help in easing all of it.
Therefore, to learn more, read ahead…
Purchase order is a common document primarily used for commercial transactions. It is an official document issued from a buyer to the seller. It carries important information along with it such as type of product, quantity of product, price of the product etc.
The document itself doesn’t act as a contract but on the contrary acts as the acceptance of order from the seller’s side.
There are several types of purchase orders. Those are:
There are several steps involved in the process before it comes to its completion. These steps are:
Adding to it, there are several types of PO invoice matching that is carried out within an organization. These are:
There are multiple reasons why an AI based automation solution is required for PO Invoice processing. These are:
An OCR has been a largely accepted way for decades as a digital solution for document data extraction. However, the needs of today have changed.
Organizations of today require a solution that can process huge volumes of unstructured data, is scalable, and handles data efficiently without any errors. IDP (Intelligent Document Processing) is capable of that and a lot more.
IDPs are AI-based document automation platforms that are capable of data extraction, verification, and storage. They provide an end-to-end solution for multiple document processing use cases and are proven to reduce TAT & improve throughput.
IDPs are a collaboration of multiple technologies such as machine learning, deep learning, natural language processing, computer vision, and robotic process automation. These technologies provide IDPs their capability to process documents intuitively and cognitively. There are multiple types of IDP vendors available in the market. However, the type of solutions they provide can be classified into two categories i.e. Customizable and Specific to a use case.
VisionERA is a SaaS-based IDP platform capable of providing end-to-end document processing experience for multiple use cases. It is an industry and use case agnostic solution because of its custom DIY workflow that can be changed and updated by its user without any coding experience. It also lets the user select the type of documents they want to use for a particular use case and provides document processing capabilities such as data extraction, data validation, triangulation logic, and storage.
With VisionERA, it is possible to create an automated document processing environment because it is compatible with multiple downstream applications. Applications such as CRM, CMS, ECM, EHR, ERP, legacy infrastructure, emails, etc. It runs using a continuous feedback mechanism that lets you handle even an exception overtime. The user just has to provide relevant feedback and VisionERA would replicate the same in coming future cases.
There are a series of steps where VisionERA can be of utmost help. These are:
There are several benefits of using VisionERA for this particular use case.
Note: Currently, we are offering VisionERA at $0 invoicing till it produces FTE outcomes. It means you can procure VisionERA at no cost and pay when it starts to deliver results.
Want to learn more about VisionERA and see how it can help with PO invoice processing? Simply schedule a demo with us at your convenience by using the CTA below or clicking here.