The generative AI hub provides access to a wide range of LLMs, offering features such as model selection and prompt management through the SAP AI Launchpad. Now, as you prepare to build more sophisticated and robust AI applications, you will have workflows that need integration for multiple tasks such as data filtering or data anonymization etc.
This is where the Orchestration Service in the generative AI hub becomes indispensable. It elevates your generative AI capabilities beyond individual LLM interactions, enabling you to design, manage, and execute complex AI workflows. This lesson will introduce you to this powerful service, clarifying its purpose, essential features, and how it ensures your AI solutions are not only intelligent but also compliant, efficient, and scalable within the enterprise.
The Orchestration Service is a managed service within SAP AI Core that provides unified access, control, and execution of generative AI models. Orchestration here refers to the systematic management and coordination of multiple AI models, services, and data flows to achieve a unified business objective. It functions as a central coordinator, managing multiple AI models and services to complete complex tasks.
The Orchestration Service streamlines the integration and management of various AI models, enabling businesses to efficiently utilize advanced AI features without changing their application code whenever models or versions are updated.
Orchestration is Essential for Enterprise AI
The Orchestration Service addresses several critical challenges inherent in building production-ready AI applications:
- Seamless Integration and Provider Agnosticism: In a rapidly evolving AI landscape, you might need to use different LLMs from various providers for specialized tasks, performance, or cost reasons. The Orchestration Service provides a harmonized API that allows your applications to interact with different foundation models without being tightly coupled to a specific provider. This means you can switch or compare models easily without altering your core application logic.
- Enhanced Control and Compliance: Enterprise solutions demand strict adherence to standards, privacy regulations, and ethical guidelines. The Orchestration Service offers built-in mechanisms to ensure compliance with SAP standards and provides centralized control over your AI workflows. For example, it provides features like data masking and data anonymization to ensure data privacy. This ensures AI operations are consistent and reliable across SAP solutions.
- Increased Efficiency and Scalability: Complex business problems often require more than a single LLM call. They require a cohesive workflow where the output of one module can automatically serve as the input for the next, streamlining processes and automating multi-step tasks. Furthermore, it supports the deployment of these orchestration workflows, providing the flexibility and scalability needed for high-volume enterprise use cases.
- Expandability and Adaptability: The dynamic nature of the AI market means new capabilities constantly emerge. Orchestration offers inherent expandability, allowing you to easily add new features like content filtering, data masking, grounding, and translation as needed, ensuring your AI solutions can adapt to changing technical and commercial requirements efficiently.
Key Features of the Orchestration Service
The Orchestration Service provides a suite of powerful modules that can be chained together. You will learn that while the sequence of these modules is structured to enforce logical processing and security, each module’s configuration offers extensive flexibility for diverse use cases. These include:
- Grounding: The Orchestration Service facilitates the integration of external, domain-specific, or real-time data sources (like your SAP systems) to enhance the contextual relevance and factual accuracy of AI model outputs. This is a critical mechanism for combating hallucinations and ensuring reliability.
- Templating: This feature allows you to create prompts with placeholders. These placeholders are dynamically populated with real-time data or context during inference, making your prompts flexible and reusable across various scenarios.
- Content Filtering: To maintain compliance and safety, the service can restrict the type of content passed to and received from generative AI models. This helps prevent the generation or processing of inappropriate or sensitive information.
- Data Masking: Supports the anonymization or pseudonymization of sensitive data before it is processed by generative AI models. Crucially, it also offers the ability to unmask data in responses when pseudonymization is used, ensuring data privacy while maintaining utility.
- Translation: For global enterprises, the service enables the translation of input and output data directly within the orchestration workflow, supporting multilingual use cases and breaking down language barriers.
Prerequisites for Using the Orchestration Service
To begin leveraging the Orchestration Service, certain foundational elements must be in place:
- SAP BTP Account: You need an active SAP BTP account as the underlying platform.
- SAP AI Core Instance: An instance of SAP AI Core must be set up within your BTP account, as the Orchestration Service runs on this infrastructure.
- Extended SAP AI Core Service Plan: An extended service plan for SAP AI Core is typically required, as the generative AI hub capabilities, including orchestration, are not usually available in free or standard tiers.
- Orchestration Deployment: Ensure that at least one orchestration deployment is created or used within a resource group, providing the executable definition of your AI workflow. A resource group will have a default deployment. You can create and use your own deployment to customize available models.
Using SDK
The SAP Cloud SDK for AI offers a straightforward way to begin using the Orchestration Service for AI-powered tasks. By setting up a template and connecting it to an LLM like GPT-5 or Gemini 2.5 Pro, users can automate processes such as translation or content generation with minimal effort. The SDK handles the orchestration logic, allowing users to define inputs, configure model behavior, and retrieve results—all through a clean and simple interface.
This setup makes it easy to build scalable and reusable AI workflows. With just a few lines of code, users can connect to the orchestration endpoint, run tasks using predefined templates, and get consistent outputs tailored to their needs. It’s a practical starting point for integrating generative AI into everyday operations.
Lesson Summary
You've now been introduced to the Orchestration Service in SAP AI Core, recognizing its pivotal role in building complex, enterprise-grade Generative AI applications. You understand its purpose in unifying access and control over diverse LLMs, and its importance in ensuring compliance, efficiency, and scalability. You've also learned about its key features like templating, content filtering, data masking, grounding, and translation, which empower you to create robust and reliable AI workflows. This foundation sets the stage for exploring its capabilities further and designing sophisticated AI solutions within the SAP ecosystem.