SAP + AI Applications
Browse practical Applications guidance in SAP + AI, organized for implementation, configuration and technical reference.
What this hub covers
Applications is a defined knowledge area within SAP + AI. This hub brings its published guides into one permanent, crawlable destination so practitioners can move from foundational concepts to configuration and operational detail without relying on a search-results page. Use the curated starting points first, then continue through the complete library for deeper implementation context.
Recommended foundations
The clearest entry points, ordered by practical usefulness.
Your First OpenAI API Project: Build a Text Summarizer
Build a Python text summarizer with the OpenAI Responses API: set up the SDK and key safely, run one request, and fact-check the result.
Read guide →Build Your First AI Workflow with n8n
Build a manually triggered n8n workflow that sends a fictional request to the OpenAI Responses API, validates the category, and stops at a review...
Read guide →Run an AI Model Locally with Ollama
Install Ollama, pull the small llama3.2:1b model, run a checkable summarization task locally, and compare it fairly with a cloud result.
Read guide →RAG Explained: Build a Small Knowledge Assistant
Build a small retrieval-augmented generation assistant with a transparent keyword retriever, source IDs in every answer, and a no-match path.
Read guide →All guides in this topic
Your First OpenAI API Project: Build a Text Summarizer
Build a Python text summarizer with the OpenAI Responses API: set up the SDK and key safely, run one request, and fact-check the result.
Build Your First AI Workflow with n8n
Build a manually triggered n8n workflow that sends a fictional request to the OpenAI Responses API, validates the category, and stops at a review...
Run an AI Model Locally with Ollama
Install Ollama, pull the small llama3.2:1b model, run a checkable summarization task locally, and compare it fairly with a cloud result.
RAG Explained: Build a Small Knowledge Assistant
Build a small retrieval-augmented generation assistant with a transparent keyword retriever, source IDs in every answer, and a no-match path.
Build a PDF Question-Answering Assistant with Sources
Extract text from a two-page PDF with pypdf, ask a model to cite page labels, and test that it admits when the document gives no answer.
Turn Unstructured Notes into a Clean Table with AI
Use OpenAI Structured Outputs with a Pydantic schema to turn fictional notes into a validated CSV, and learn why valid shape is not proof of correct...