I've been building AI agents for a while and the memory problem kept bugging me. Every time a conversation ends, your agent forgets everything. The standard fix is cramming thousands of tokens of conversation history into every prompt. It's slow, expensive, and most of it isn't even relevant.
So I looked at what's out there. Mem0, Zep, Supermemory. They all do basically the same thing: take text, embed it as blobs, throw it in a vector database. It works, sort of. But there's no structure. You can't look up a specific piece of knowledge. You can't version it. You can't organize it. And they charge you ~$0.002 per operation on YOUR API key because they're running LLM completions for every read and write.
Intercepts deterministic queries before they hit your LLM and resolves them locally in <5ms for $0. Math, timezones, currency, files, dates - 70% token savings on typical workflows. Free forever for core rules.
ZeroRules uses pattern matching to catch calculator problems, timezone lookups, currency conversions, and file operations before they burn tokens. Resolves locally with zero latency. Works with OpenClaw.
