Support bots are the single best caching workload in software
Nowhere else do thousands of people ask the same fifty questions, all day, in every phrasing imaginable. Crowkis was practically designed in a support queue.
Open any support transcript archive and the pattern leaps out: refunds, password resets, shipping windows, plan changes — the same fifty intents wearing thousands of phrasings. A support LLM without semantic caching purchases the refund-policy answer hundreds of times a day, at full token price and full multi-second latency, because each customer spells it differently.
Crowkis turns that head of the distribution into sub-millisecond hits. Intent classification recognizes the factual question, the template abstracts away order numbers and dates, the vector index finds the canonical answer, and the confidence gate confirms the match before a byte is served. The customer gets an instant answer; your invoice gets nothing.
Every paraphrase is a fresh bill — unless the cache understands meaning.
Safety matters double in support, because mistakes face customers directly. The gates earn their keep here: 'cancel my account' never serves the cached 'pause my account' answer, tenant walls keep client A's policy out of client B's chat, and freshness policies expire the old pricing the moment you change it.
The bottom line
Teams running support traffic see the highest hit rates we measure — repetition is the workload's nature. If you deploy Crowkis on exactly one thing, deploy it here, and watch the dashboard pay for the afternoon by dinner.