Streamline Invoice Handling with Oracle Integration Cloud & AI

Table of Contents:

1. Introduction
2. Demo Overview
3. Ingest and Automate
   • Using Oracle Integration Cloud Service
   • File Server SFTP
   • Scheduled Integration
4. Classify and Extract
   • Using OCI AI Document Understanding Service
   • Pre-trained Models for Invoices
   • Key Value Extraction
   • Bounding Polygon and Confidence Score
5. Store
   • Using Oracle Autonomous Database Service
   • Invoice Data Storage
6. Invoice Understanding Process
   • Manual Workflow for Failed Records
   • Approval Process and Backend System Integration
7. Conclusion

Article:

Automate Invoice Handling Process with Oracle Integration Cloud and AI

Technology continues to revolutionize various aspects of business operations, and one area that has undergone significant transformation is invoice handling. Manual invoice processing can be time-consuming, error-prone, and inefficient. However, with the help of Oracle Integration Cloud (OIC) and AI technologies, businesses can automate and streamline their invoice handling process.

1. Introduction

In this article, we will explore a demo showcasing how You can automate the invoice handling process using Oracle Integration Cloud and the AI Document Understanding service. This process consists of three main parts: ingest and automate, classify and extract, and store.

2. Demo Overview

The demo revolves around a fictional Scenario where invoices need to be processed and stored efficiently. To achieve this, Oracle Integration Cloud Service (OIC) and the AI Document Understanding service are employed.

3. Ingest and Automate

The first part of the process involves ingesting and automating the invoices. OIC, equipped with a built-in file server SFTP, is used to store all the incoming invoices. A scheduled integration within OIC periodically checks for new invoices and processes them. It then calls the Document Understanding service for classification and key value Data Extraction. The data that is classified correctly Based on defined parameters and confidence codes is stored in an ATP database or any other ERP system of choice. In case of failed records, a manual workflow is created using OIC process, allowing for manual intervention and data correction.

4. Classify and Extract

The Second part of the process focuses on classifying and extracting data from the invoices. The OCI AI Document Understanding service offers pre-trained models specifically designed for invoices, along with other document types such as driver licenses and passports. For this demo, the pre-trained model for invoices is used. It extracts around 28 key value pairs, including vendor name, vendor address, and invoice total. Additionally, it extracts 10 key values for line items, such as item amount and quantity. The service provides a bounding polygon, indicating the location of the extracted information within the document, along with a confidence score for each extraction.

5. Store

The extracted invoice data is stored in the Oracle Autonomous Database service in this demo. However, in real-life scenarios, it can be stored in any other ERP system, such as Fusion ERP, E-Business, SAP, or others. The autonomous database facilitates efficient storage and retrieval of invoice information.

6. Invoice Understanding Process

To ensure accuracy and completeness, a simple invoice understanding process is implemented. Upon receipt of an invoice, it undergoes a review by an invoice reviewer. The reviewer can manually intervene and correct any missing or incorrect information. The invoice is then submitted for approval, where it is verified by the manager. If everything is in order, the data is sent back to the database for storage. In cases where information is missing, a process is triggered, allowing for manual intervention and data entry.

7. Conclusion

Automating the invoice handling process using Oracle Integration Cloud and AI technologies brings numerous benefits to businesses. It reduces manual errors, increases efficiency, and accelerates invoice processing. The integration of the AI Document Understanding service enables accurate classification and data extraction from invoices. With the Oracle Autonomous Database service, businesses can securely store and retrieve invoice information.

In conclusion, businesses can optimize their invoice handling process, reduce costs, and improve productivity by leveraging the power of Oracle Integration Cloud and AI technologies.

FAQ

Q: Can this invoice handling process be customized for different ERP systems? A: Yes, the demo showcases the process using the Oracle Autonomous Database service. However, the process can be easily adapted to work with other ERP systems such as Fusion ERP, E-Business, SAP, or any other desired system.

Q: Is manual intervention required for every invoice? A: No, manual intervention is only required for invoices that fail to meet certain criteria or have missing information. The AI Document Understanding service and the automated workflow minimize the need for manual intervention.

Q: Can the key value extraction be customized for specific business requirements? A: Yes, the key value extraction can be customized based on business requirements. The pre-trained models provided by the AI Document Understanding service can be fine-tuned or additional models can be trained to extract specific information as per business needs.