Solution
RAG & search
“High-volume, long-context workloads that are ruinously expensive on frontier models.”
Retrieval pipelines generate millions of large-context requests where economical models perform nearly as well as frontier ones. Run embedding, reranking and synthesis on the cheapest capable model per step, through one API, and swap models as the price-performance frontier moves.
Outcomes
What changes with RootInference
- Long-context synthesis at economy-tier prices — 1M tokens for 5–15 credits
- Per-step model selection across the whole retrieval pipeline
- Model swaps as prices drop, with zero pipeline changes