SAP AI Glossary
Plain-language definitions of AI terms — with real SAP examples. No coding background required.
Agent / AI Agent
AI that takes a sequence of actions — not just answers questions.
An invoice-processing agent calls SAP APIs to check POs, GRs, and tolerances — then releases or escalates automatically.
A2A (Agent-to-Agent)
Multiple specialised AI agents collaborating on a complex task.
A coordinator agent delegates to a Finance agent and an MM agent, then combines their findings into a procure-to-pay analysis. SAP's BTP AI architecture supports A2A natively.
API (Application Programming Interface)
How software systems talk to each other.
SAP's BAPIs, OData services, and RFCs are all APIs. When AI connects to SAP data, it does so through an API.
Context Window
How much text an LLM can hold in mind at once — your entire conversation plus any documents shared.
Pasting a large ABAP dump or a long transport log can exceed the context window. The AI may truncate or miss earlier parts of the conversation.
Embeddings
Text converted into numbers (vectors) that represent its meaning — enabling semantic search.
Your SAP procedures document gets split into chunks, each chunk gets an embedding, and those embeddings are stored in a vector database. The AI retrieves relevant chunks by meaning, not just keyword match.
Fine-tuning
Training an LLM further on your specific data to make it better at specific tasks.
A fine-tuned SAP model trained on thousands of SAP Notes would know SAP terminology more deeply. Less common than RAG — fine-tuning is expensive and requires stable, high-quality training data.
Hook
A function that runs before or after an event to add custom logic — intercept, validate, enrich.
A pre-execution hook on an invoice-release agent checks: is the variance within auto-release tolerance? If not, the hook blocks the action and forces human approval. Analogous to BAdIs in ABAP.
LLM (Large Language Model)
The AI system that understands and generates text.
SAP Joule is a product layer built on top of LLMs. Claude (Anthropic) and GPT-4 (OpenAI) are the underlying models. SAP AI Core can host and run LLMs inside your BTP landscape.
MCP Server (Model Context Protocol)
A universal connector that exposes your SAP system's data and actions to any AI agent via a standard protocol.
An ABAP MCP server exposes SAP function modules as AI-callable tools. A CAP MCP server exposes BTP services. Any MCP-compatible AI agent (Claude, Joule, etc.) can then call your SAP system through these tools.
Prompt
Your instruction or question to an AI.
"Explain document splitting in SAP FI" — that's a prompt. The quality of your prompt directly affects the quality of the AI's answer.
RAG (Retrieval-Augmented Generation)
AI that retrieves relevant documents before generating an answer — grounding responses in your actual data.
Before answering "What is our intercompany invoicing process?", a RAG system retrieves your internal SOP from the document store, then generates an answer based on your actual procedure — not generic SAP theory.
System Prompt
Hidden instructions that define how an AI behaves — its role, rules, and constraints.
Joule's behaviour is shaped by a system prompt written by SAP engineers. The AI Assistant on this platform has a system prompt that tells it to be an SAP expert and stay on topic.
Token
The AI's unit of text — roughly ¾ of a word. LLMs process and generate tokens, not characters or words.
AI APIs are priced per token. A long SAP ABAP error trace is thousands of tokens — understanding this helps you use AI tools cost-effectively.
Tool Use / Function Calling
The mechanism that lets AI agents call external systems — defined functions with names, descriptions, and parameters.
An agent with a tool called `post_fi_document` can call BAPI_ACC_DOCUMENT_POST in SAP. The tool definition tells the AI what the function does, what parameters it needs, and what it returns.
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