Not a cheaper way to call the LLM. A way to not call it again. CacheCore makes equivalent agent reasoning steps free after the first one.
HOW IT WORKS
Point your LLM client at Cachecore. No SDK changes, no rewrites.
Equivalent agent steps (same role, semantically equivalent input) match on L1 exact or L2 semantic cache. Typically under 20ms round-trip.
Pay for the first call. Never the repeat. Watch costs collapse.
FEATURES
When agents repeat the same reasoning step — same role, same context, semantically equivalent input — CacheCore returns the result instantly. The thinking already happened. You don't pay for it twice.
Multi-agent pipelines run the same sub-tasks constantly: document checks, tool calls, synthesis steps. CacheCore collapses redundant work across the entire agent graph, not just individual calls.
OpenAI-compatible. Works with LangChain, CrewAI, LangGraph, AutoGen, and OpenClaw. Point your base_url at CacheCore and you're done.
40–70% fewer billable tokens in production agent workloads. The savings compound with every agent step that hits cache instead of the model.
GUIDES
How CacheCore cuts synthesis latency from 5 seconds to 19 milliseconds for RAG agents, without touching your prompting logic.
Read guide →Cut LLM costs for multi-agent OpenClaw workflows with one config change. No code modifications required for basic integration.
Read guide →We're looking for early testers. No credit card required.