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guidesMay 21, 2026· 4 min read

Cache Ollama in your onboarding assistant with Crowkis

Building onboarding assistants on Ollama? Add a semantic cache so every new hire asking the same first questions stop costing full price.

Onboarding assistants built on Ollama share one problem: every new hire asking the same first questions. Each repeat is a full-price Ollama call for an answer you already have.

Put a semantic cache in front. Point Ollama's base URL at the Crowkis OpenAI-compatible gateway, or wrap the call in get-or-compute, and reworded repeats are served from cache, no rewrite of your onboarding assistants logic.

Ollama + Crowkis
base_url = "http://127.0.0.1:6380/v1"   # Crowkis gateway, semantic cache in front
In plain words: The onboarding assistants keep working exactly as before; the repeats just stop hitting the model.

On repetitive traffic this cuts costs up to 60-70% on repetitive workloads, and every hit carries a confidence score so reuse stays safe. Runs self-hosted with zero egress, nothing leaves your machine.