Case 07
RAG Knowledge Platform
RAG Knowledge Platform: Problem: Engineering knowledge is spread across repositories, runbooks, tickets, architecture notes, and project history. Constraints: Source freshness, citation quality, chunking, access boundaries, hallucination control, and explainable answers. Architecture: Curated ingestion pipeline with markdown exports, project metadata, embedding-ready documents, source references, and fallback local answers. Result: The AI assistant can answer infrastructure questions with project context, sources, and a safer boundary around what it knows.
- Problem
- Engineering knowledge is spread across repositories, runbooks, tickets, architecture notes, and project history.
- Constraints
- Source freshness, citation quality, chunking, access boundaries, hallucination control, and explainable answers.
- Architecture
- Curated ingestion pipeline with markdown exports, project metadata, embedding-ready documents, source references, and fallback local answers.
- Result
- The AI assistant can answer infrastructure questions with project context, sources, and a safer boundary around what it knows.
Related topics: AI infrastructure, Kubernetes/EKS, GitOps, Terraform, observability, platform engineering, cloud architecture.