Crowkis for AI search: cut cost and latency
AI search are full of popular queries hit again and again. A safe semantic cache turns that repetition into instant, free hits.
AI search are one of the most repetitive LLM workloads there is: popular queries hit again and again. Every repeat is a full-price model call for an answer you already produced.
What Crowkis changes
Crowkis sits in front of your model and reuses answers by meaning, not exact text, so a reworded question still hits. It adds structural matching, per-hit confidence, freshness control, and tenant isolation, so reuse is safe, not just cheap.
In plain words. For AI search, the repetition is the bill. Remove the repetition and the bill drops.
On workloads like this, semantic caching cuts LLM costs up to 60-70% on repetitive workloads, and hits return in well under a millisecond, so AI search feel faster too. Community edition ships at full power, free to run.
The cheapest, fastest answer is the one you already have and can safely reuse.