Bringing Intelligence to Your Integration Flows

In today’s fast-paced business landscape, simply moving data between systems is no longer enough. Modern integration needs to be smart, adaptive, and proactive.

With the power of SAP Integration Suite and AI services, your integration flows can now go beyond connectivity — they can analyze, validate, and make intelligent decisions in real time.

Imagine workflows that don’t just pass information but understand context, detect anomalies, and take action automatically. Whether it’s ensuring compliance, assessing risk, or enriching business processes with AI insights, intelligent integration is transforming how organizations operate.

This new era of integration enables:

• Dynamic decision-making based on live data
• Automated validation and risk checks
• Augmented workflows that act like intelligent assistants embedded within your processes

With AI-powered integrations, your iFlows are no longer silent conveyors of data — they become active participants in your business processes, helping drive efficiency, accuracy, and smarter outcomes.

Key Features of AI Adapter in SAP Integration Suite

AI Adapter in SAP Integration Suite: Extends iFlows to generative AI services.

• Variants:
  • AICore-GenAIHub: Integrates with SAP AI Core for multiple GenAI models via a unified API.
  • Custom-OpenAI-REST: Connects to OpenAI’s APIs for text generation and classification.
• Features: Secure authentication (OAuth2/API Key), dual configuration (Basic/Advanced), multi-model orchestration.
• Applications: Document processing, content generation, decision support.

 

Example Scenario: Real-Time Tax Compliance and Fraud Risk Assessment

In this scenario, sales orders arrive from multiple channels such as e-commerce, CRM, or EDI.Before posting to SAP, each order must be validated for tax compliance and fraud risk. 

Key Steps in the iFlow:

1. Tax and Summation Validation:
   1. Verifies that each item is taxed correctly according to state tax laws (e.g., a “Snack Bar” in California).
   2. Ensures that totals match (subtotal + taxAmount = grandTotal).
2. Fraud Risk Assessment:
   1. Calculates a fraud score (0.0–1.0) based on discrepancies or conflicting data.
   2. Identifies high-risk orders.
3. Incident Categorization and Action:
   1. If an issue is detected, a second AI call categorizes the incident as High, Medium, or Low risk.
   2. Automatically generates a Jira ticket for tracking non-compliant or high-risk orders.
   3. Compliant orders are allowed to flow into SAP S/4HANA, while non-compliant orders are blocked.

This scenario demonstrates intelligent automation within SAP Integration Suite, enabling real-time compliance checks and reducing manual effort.

Stage 1: AI Call #1 

Every order is processed by the first AI model. For this request, we use UI Configuration to select and map only the necessary fields from the incoming sales order into the AI request.

For demonstration purposes, the sales order payload is defined here in the content modifier

AI Adapter :

Utilize the AI Adapter for GenAI Hub Connectivity

 

 

Refer to this document for Configuring the AI Adapter as above

AI Adapter Configuration

Use AI Adapter to Prompt an LLM

Analyze the following sales order data for tax compliance and fraud risk, and respond only in this JSON format: {“taxComplianceCheck”: “true or false”, “summationCheck”: “true or false”, “taxDiscrepancyAmount”: “number”, “fraudRiskScore”: “number”, “reason”: “string”}. Triple backticks are used to clearly highlight the review text.

AI Output

JSON to XML Converter : AI model returns the response in JSON format, it contains various fields, but our focus is on the “content” field which has the result. It’s easier to extract the field from a XML file rather than a JSON. Hence there is a usage of JSON to XML Converter.

Groovy Script to Extract the Fields and Save only the required AI output 

Formatted Output:

Stage 2: The Router & The Final Decision

Next is the Router—this is where the main decision happens, making sure we handle orders in the smartest way possible:

• Good Order? (Green Light): If there are NO errors and the is low (below 0.5), the order is instantly approved and sent straight to S/4HANA. Success! (This is the fastest path for most orders.)
• Bad Order? (Special Handling): If there’s any issue, the flow triggers AI Call #2. 

AI Call #2 

For this request, we set the payload source to Exchange Body, so the full message payload is sent directly to the categorization AI, which quickly determines the urgency of the issue.

Incident Categorization Payload

This utilizes the entire message body as input for the subsequent AI step.

 

 

Formatted Output:

Jira Payload Creation in Content Modifier

Jira Adapter Call:

 

Jira ticket is created :

 

See the Flow! 

This is where the magic becomes real. The IFlow below shows exactly the whole process.

Useful Links:

AI Adapter 

AI Adapter Guide.

Getting Started with GenAIHub

Consumption of GenAI models Using Orchestration

SAP AI Core

Jira Adapter Guide