AGENT INFRASTRUCTURE

Stop paying for the
same LLM call twice.

One config change · 70ms on cache hit · $0 on every repeat
~/app
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$ HIT

HOW IT WORKS

[01]

DROP IN

Point your LLM client at Cachecore. No SDK changes, no rewrites.

[02]

CATCH

Every call gets fingerprinted. Exact matches return in 70ms. Near-identical ones match semantically and return in under a second.

[03]

SAVE

You paid for the first answer. Every time that same question comes back, the answer is free.

FEATURES

Two layers of cache

Word-for-word repeats return in 70ms. Near-identical calls match semantically and return in under a second. Both skip the API completely. You get the answer, not the bill.

Works across your whole pipeline

Multi-agent systems repeat the same work constantly. Document checks, tool calls, synthesis steps. CacheCore catches duplicates across every agent in your graph, not just within a single session.

One config change

OpenAI-compatible. Works with LangChain, CrewAI, LangGraph, AutoGen, and OpenClaw. Point your base_url at CacheCore and you're done.

40 to 70% fewer API calls

In most agent workloads, the majority of calls are repeats. CacheCore catches them before they reach the model. The savings add up fast, and compound with every agent you add.

GUIDES

70ms
Exact cache hit (L1)
650ms
Semantic cache hit (L2)
70%
Avg. cost reduction

Stop paying for the
same LLM call twice.

Request Access

We're looking for early testers. No credit card required.