Enable category managers to populate content recommendations from large language models (LLM) integration based on contextual and dynamic questions for tools such as category segmentation, category market dynamics and category cost structure.

Category managers save time and effort by receiving tailored strategy recommendations based on their inputs, allowing them to focus on making informed, strategic decisions rather than manually analyzing data. This enhances efficiency, improves decision-making, and helps drive better procurement outcomes.

Category managers can generate summaries of category strategy documents in SAP Ariba Category Management. These AI-enhanced summaries provide a quick overview, highlighting key points without the need to manually review details across all sections of the approval documents. Category managers can refine these summaries and send them for approval, improving decision-making. Additionally, they can regenerate category strategy details recommendations when the data in the strategy and plan tools is updated.​

Enabling users to input minimal data, such as a title and brief summary, and then leverage generative AI to produce comprehensive SOW descriptions.​

Enable suppliers to respond to RFIs in a consistent and timely manner, even when dealing with complex and detailed requests.​

This feature analyzes the documents attached to custom release checks required within the batch release process. This reduces the manual effort for the Qualified Persons (QP) by proposing AI generated results directly in the UI for faster review, check of references and sign off. The solution empowers the QPs to save a significant amount of time as extensive search in the big documents is not needed anymore. Instead, end users can focus on reviewing the provided recommendations, while keeping the role of the final decision-maker.​

The feature enables SAP Integrated Product Development users to automatically create hotspots on 2D drawings, and associate with back-end business data, which empowers customers to streamline the digital transformation journey of their legacy drawings.​

Visual inspections help to ensure correct and complete assembly, shape or appearance attributes, and defect-free materials such as scratches, dents, or other flaws. Identifying nonconformances early and taking the right countermeasures helps your organization produce high-quality products. The apps and plugins available let you create both manual and machine learning-based visual inspections.​

Purchasers can predict delivery dates for purchase order items based on historical data, using Intelligent Scenario Lifecycle Management. Based on multiple parameters, the system can predict a date by which the supplier can deliver the material.​

Provide suppliers with an intelligent way to process rejected invoices that are submitted through the SAP Business Network. Categorize the invoices that are rejected into appropriate rejection categories which allows the invoices to be reprocessed in a methodical manner.​

Let AI recommend maintenance orders that solved similar incidents from maintenance history. You select one to copy to create a new maintenance order.

Automatically match packaging-accounts with account-statements with Machine Learning-supported algorithm.​