Cache LangGraph in your research assistant with Crowkis
Building research assistants on LangGraph? Add a semantic cache so overlapping literature and summary questions 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 research assistants on LangGraph? Add a semantic cache so overlapping literature and summary questions stop costing full price.
Add a semantic cache to LiteLLM so repeated and reworded questions are served for free, no rewrite, self-hosted.
Every new API is a tax on adoption: clients, docs, muscle memory, tooling. RESP3 meant inheriting twenty years of all four on day one.
Caching across customers multiplies savings and multiplies risk. Tenant isolation has to be architecture, not a WHERE clause.
Building RAG document search on Spring AI? Add a semantic cache so the same questions re-running retrieval over the same corpus stop costing full price.
Building legal document assistants on the OpenAI Python SDK? Add a semantic cache so the same clauses and questions across matters stop costing full price.
Building data analysis agents on DSPy? Add a semantic cache so repeated tool calls and the same analytical questions stop costing full price.
Building contract analysis tools on LangGraph? Add a semantic cache so the same clause questions across documents stop costing full price.
Durable, per-user memory for LiteLLM agents that survives restarts and consolidates contradictions, self-hosted, zero egress.
A cache of LLM traffic is a cache of whatever users typed, including PII. CPII reports what personal data is present and executes right-to-erasure, so compliance is a command, not a project.
Model prices vary 50x for overlapping quality on easy queries. The arbitrage router exploits the spread automatically, with a quality bar you set per intent.
Building internal copilots on Spring AI? Add a semantic cache so employees asking overlapping questions of the same knowledge base stop costing full price.
Building education tutors on the OpenAI Python SDK? Add a semantic cache so students asking the same concepts thousands of times stop costing full price.
Building HR assistants on DSPy? Add a semantic cache so the same policy questions from every employee stop costing full price.
Building onboarding assistants on LangGraph? Add a semantic cache so every new hire asking the same first questions stop costing full price.
Add a semantic cache to Ollama so repeated and reworded questions are served for free, no rewrite, self-hosted.
Memcached is the purest cache ever written, and purity is exactly the problem when your keys are sentences.
Building chatbots on Spring AI? Add a semantic cache so high-volume conversational traffic that repeats constantly stop costing full price.
Building multi-agent systems on the OpenAI Python SDK? Add a semantic cache so a swarm of agents asking overlapping questions stop costing full price.
Building IT helpdesk bots on DSPy? Add a semantic cache so the same tickets and fixes, endlessly stop costing full price.