ai-data-engineering

What problem does it solve?

This Skill enables the creation and management of robust data infrastructure essential for AI/ML systems, including RAG pipelines, feature stores, and embedding generation.

Core Features & Use Cases

• RAG Pipelines: Build end-to-end RAG systems from ingestion to evaluation.
• Feature Stores: Implement ML feature serving with Feast to prevent training-serving skew.
• Embedding Generation: Create high-quality embeddings using state-of-the-art models.
• Orchestration: Manage complex data workflows with Dagster or Prefect.
• Use Case: Develop a RAG pipeline for customer support documentation, enabling semantic search and question answering over your knowledge base.

Quick Start

Use the ai-data-engineering skill to set up a basic RAG pipeline by chunking documents and generating embeddings.