Invoice Processing use case
Summarize
Summary of Invoice Processing use case
The Invoice Processing use case in the Accounts Payable Operations integration with Document Intelligence enables automated extraction of invoice data from email attachments. It is designed for users with the Accounts Payable Specialist role to interact with the extracted invoice information within the Document Intelligence workspace. This use case is read-only and cannot be edited.
Show less
Key Features
- Field Extraction: Contains a predefined list of invoice and invoice line fields to extract data from invoice documents, such as invoice date, with configurable data type handling (e.g., ambiguous date formats).
- Field Groups: Includes an Invoice Lines field group that maps extracted invoice line data to the Invoice Line Stage target table for structured storage.
- Document Tasks: Provides tasks to train the Document Intelligence model to improve accuracy in identifying invoice information.
- Integration: Utilizes the DocIntel Extract Values Flow (Invoice processing v1.2) to populate extracted data into invoice and invoice line stage records and update the invoice stage status to “Processing completed.”
- Access: Available via the ServiceNow interface under All > Document Intelligence > Use Cases > DO NOT USE - Invoice processing.
Practical Implications for ServiceNow Customers
This use case automates the data extraction process from invoice documents, reducing manual data entry and improving processing efficiency in Accounts Payable operations. Customers can expect structured invoice data stored in appropriate stage records, facilitating streamlined invoice processing workflows. Since the use case is read-only, customization is managed by platform administrators via the Document Intelligence administration menu.
Accounts Payable Operations integration with Document Intelligence provides the DO NOT USE - Invoice Processing use case.
The DO NOT USE - Invoice Processing use case contains the list of invoice fields to extract data from invoice attachments and stores this data in the invoice stage record. It also contains an extraction flow that populates the extracted invoice data into the invoice stage and invoice line stage records and updates the Invoice stage status to Processing completed.
You can access this use case by navigating to .
The DO NOT USE - Invoice Processing use case includes the following information.
| Use case information | Description |
|---|---|
| Fields | Contains the list of invoice and invoice line fields to extract information from an invoice document. A field is a single piece of information to extract from an invoice document. In the use case, invoice date is of data type
"Date field". For example, in case of ambiguous date format such as 01-02-2024, the use case (the current use case) interprets the date as month followed by day or vice versa through the DI administration configuration menu. The
platform admin [platform_ml_di.admin] manually configures the use case in the DI administration menu. For more information on the DocIntel fields used to extract data, see . For the list of invoice and invoice line fields included in the DO NOT USE - Invoice Processing use case, see List of invoice and invoice line fields included in the use case for Accounts Payable Operations integration with Document Intelligence. |
| Field Groups | Includes the Invoice Lines field group that maps to the Invoice Line Stage [sn_ap_ic_invoice_line_stage] target table where the extracted invoice line information from the invoice document is stored. |
| Document tasks | Includes a document task to train the Document Intelligence model to identify the correct information to extract from an invoice document. |
| Integration | Maps to the DO NOT USE - Invoice processing use case that contains the DocIntel Extract Values Flow - Invoice processing v1.2 - Invoice Processing v1.2 extraction flow, which populates the extracted invoice data into the invoice stage and invoice line stage records. It also updates the Invoice stage status to Processing completed. |