ZenLLM
RAG Cost Optimization for Retrieval-Heavy Workloads
ZenLLM helps teams see where retrieval overhead, repeated context, and oversized prompts are pushing RAG costs higher than they need to be.
Start with the free audit
Start with a free, self-serve cost read before connecting telemetry or creating a workspace.
Start the free audit immediately instead of stopping at a capture form.
Save company context only if you want the benchmark prefilled and the follow-up saved.
Measure how retrieval, prompt size, and model choice combine into the real RAG bill.
Find routes where caching or slimmer context windows pay back quickly.
Separate retrieval overhead from actual model cost so the next fix is obvious.
What to evaluate next
Use the audit result to move from a broad cost question into the specific routing, ownership, or chargeback issue most worth validating.
Prompt caching ROI: Estimate whether repeated RAG context is expensive enough to cache.
Model routing optimization: Pair retrieval fixes with better route-level model choice.
AI cost visibility: Break down the bill by route, retrieval path, and model.