What this guide shows
This poster frames retrieval-augmented generation as a full-stack systems problem, not just an application pattern.
It helps visualize:
- ingestion, chunking, and embedding flow
- vector storage and retrieval layers
- model serving and inference paths
- GPU-aware platform and infrastructure dependencies
- the operational controls needed for observability and scale
Best for
- engineers designing production RAG systems
- teams mapping where GPU acceleration matters in retrieval pipelines
- architects aligning platform, serving, and data-layer decisions
Why it matters
RAG quality depends on more than prompts and models. Latency, throughput, retrieval design, serving topology, and infrastructure controls all shape the final system behavior.