Cache LlamaIndex in your AI search with Crowkis
Building AI search on LlamaIndex? Add a semantic cache so popular queries hit again and again stop costing full price.
Notes from the nest · 980 posts
Engineering notes written by the people building Crowkis. Comparisons, use cases, economics, internals, security, operations, and nothing written just to rank.
Building AI search on LlamaIndex? Add a semantic cache so popular queries hit again and again stop costing full price.
Add a semantic cache to the Mistral SDK so repeated and reworded questions are served for free, no rewrite, self-hosted.
Users expect LLM answers to arrive as a typing stream. CGETSTREAM serves cached answers chunk by chunk, so a sub-millisecond hit doesn't break the interface's rhythm.
Voice gives you about a second before silence feels broken. Model round-trips don't fit. Cache hits do, with room to spare for the speech stack.
Building data analysis agents on Spring AI? Add a semantic cache so repeated tool calls and the same analytical questions stop costing full price.
Building contract analysis tools on the OpenAI Python SDK? Add a semantic cache so the same clause questions across documents stop costing full price.
Building customer support bots on Instructor? Add a semantic cache so repeat questions from every customer, all day stop costing full price.
Building ecommerce assistants on LlamaIndex? Add a semantic cache so the same product and policy questions across shoppers stop costing full price.
Durable, per-user memory for the Mistral SDK agents that survives restarts and consolidates contradictions, self-hosted, zero egress.
Building HR assistants on Spring AI? Add a semantic cache so the same policy questions from every employee stop costing full price.
Building onboarding assistants on the OpenAI Python SDK? Add a semantic cache so every new hire asking the same first questions stop costing full price.
Building coding assistants on Instructor? Add a semantic cache so the same explanations and boilerplate reasoning, dozens of times a day stop costing full price.
Building healthcare Q&A assistants on LlamaIndex? Add a semantic cache so recurring policy and triage questions stop costing full price.
Add a semantic cache to LangChain.js so repeated and reworded questions are served for free, no rewrite, self-hosted.
Google bills cached context per token per hour, a parking meter for your own prompts. Compare that with a cache you simply own.
Building IT helpdesk bots on Spring AI? Add a semantic cache so the same tickets and fixes, endlessly stop costing full price.
Building meeting-notes summarizers on the OpenAI Python SDK? Add a semantic cache so similar summaries requested repeatedly stop costing full price.
Building RAG document search on Instructor? Add a semantic cache so the same questions re-running retrieval over the same corpus stop costing full price.
Building legal document assistants on LlamaIndex? Add a semantic cache so the same clauses and questions across matters stop costing full price.
Durable, per-user memory for LangChain.js agents that survives restarts and consolidates contradictions, self-hosted, zero egress.