How does this skill handle data privacy and security?

It includes detailed patterns for implementing data masking (PII protection) and content filtering to ensure enterprise-grade security and compliance.

Does this skill support multi-provider LLM integration?

Yes, it covers the Generative AI Hub which allows unified access to models from Azure OpenAI, AWS Bedrock, GCP Vertex AI, Mistral, and more.

Is Retrieval-Augmented Generation (RAG) supported?

Absolutely. The skill includes guidance for grounding LLMs with external data sources like SharePoint, S3, and SAP Build Work Zone.

Can I use this for traditional Machine Learning training?

Yes, it provides documentation and templates for managing ML training pipelines using Argo Workflows on SAP AI Core execution engines.

What is the primary benefit of using the sap-ai-core skill?

It provides standardized guidance and implementation patterns for managing the full AI lifecycle on SAP BTP, from LLM orchestration to ML training.

SAP AI Core

Name: SAP AI Core
Author: secondsky

bysecondsky

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Data Science & ML

Deploys and manages enterprise AI/ML workloads, Generative AI Hub models, and orchestration pipelines on SAP BTP.

About

This skill provides expert guidance for implementing AI capabilities on the SAP Business Technology Platform using SAP AI Core and SAP AI Launchpad. It enables developers to orchestrate large language models (LLMs) from multiple providers, implement Retrieval-Augmented Generation (RAG) with grounding, manage ML training pipelines using Argo Workflows, and ensure enterprise compliance through content filtering and PII data masking. Whether building AI-powered SAP applications or managing complex machine learning lifecycles, this skill offers standardized patterns for deployment, tool calling, and structured outputs within the SAP ecosystem.

Key Features

Modular orchestration for templating, grounding, and data masking
Argo Workflows integration for scalable ML training and inference
End-to-end RAG implementation with vector database grounding
Enterprise-grade PII protection and Azure content safety filtering
11 GitHub stars
Unified access to multi-provider LLMs including GPT-4o, Claude, and Llama

Use Cases

Implementing context-aware RAG systems using corporate data from SAP DMS or S3
Automating ML model training and deployment pipelines on SAP BTP
Building secure, PII-compliant AI assistants for SAP enterprise applications

About

Key Features

Modular orchestration for templating, grounding, and data masking
Argo Workflows integration for scalable ML training and inference
End-to-end RAG implementation with vector database grounding
Enterprise-grade PII protection and Azure content safety filtering
11 GitHub stars
Unified access to multi-provider LLMs including GPT-4o, Claude, and Llama

Use Cases

Implementing context-aware RAG systems using corporate data from SAP DMS or S3
Automating ML model training and deployment pipelines on SAP BTP
Building secure, PII-compliant AI assistants for SAP enterprise applications