SilkRouter RAG Pipeline: Production Setup

RAG architecture

A SilkRouter RAG pipeline should keep retrieval, prompt assembly, model routing, and monitoring as separate responsibilities. That makes quality problems easier to isolate.

The request path is simple: retrieve relevant chunks, build a constrained prompt, choose the model, send the call through SilkRouter, then log usage and answer metadata.

• Retrieval decides what context enters the prompt.
• Routing decides which model handles the answer.
• Monitoring explains cost, failures, latency, and model mix.

Retrieval quality

Most RAG failures start before the model call. Bad chunking, weak metadata, stale documents, or broad search results make even strong models produce vague answers.

Keep an evaluation set with known questions, expected source documents, and unacceptable answer patterns. Review retrieval misses before blaming the model.

Model routing

Use cheaper or faster models for simple lookup answers and reserve stronger models for synthesis, conflict resolution, and customer-facing final responses. The routing rule should follow task risk, not provider preference.

SilkRouter helps centralize the model path, API keys, prepaid balance, and usage records so RAG cost does not disappear across separate provider dashboards.

Rollout checklist

Ship RAG in stages. Run internal questions first, then limited customer traffic, then broader rollout after retrieval precision and cost are visible.

• Log document IDs, model, status, tokens, latency, and answer source coverage.
• Fail closed when retrieval confidence is too low.
• Cap context size and output length before launch.
• Review failed calls and no-answer cases weekly.