
Crowkis
The smart, Rust-built LLM cache and agent memory layer
What it does
Crowkis is a Redis-compatible, ultra-fast LLM cache built in Rust. Traditional caches fail with AI because minor prompt variations cause cache misses. Crowkis fundamentally understands semantic query intent, evaluates if a cached response is safe and relevant to reuse, and acts as an intelligent agent memory layer. Maximize your response speeds, slash API token costs, and prevent stale context or hallucinations across your LLM workloads securely
Does a similar job
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Multi-tier exact-match cache for AI agents backed by Valkey or Redis. LLM responses, tool results, and session state behind one connection. Framework adapters for LangChain, LangGraph, and Vercel AI SDK. OpenTelemetry and Prometheus built in. No modules required - works on vanilla Valkey 7+ and Redis 6.2+. Shipped v0.1.0 yesterday, v0.2.0 today with cluster mode. Streaming support coming next. Existing options locked you into one tier (LangChain = LLM only, LangGraph = state only) or one framework. This solves both. npm:…
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I keep running in the same problem of each AI app “remembers” me in its own silo. ChatGPT knows my project details, Cursor forgets them, Claude starts from zero… so I end up re-explaining myself dozens of times a day across these apps. The deeper problem 1. Not portable – context is vendor-locked; nothing travels across tools. 2. Not relational – most memory systems store only the latest fact (“sticky notes”) with no history or provenance. 3. Not yours – your AI memory is sensitive first-party data, yet you have no control over where it lives or how it’s queried. Demo video:…


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