I built GrantAi because RAG kept failing me. Vector similarity returns content
that "looks like" your query — but similar isn't correct. Ask for "HIPAA
penalties" and you might get GDPR fines because the embeddings are close.
GrantAi is deterministic. Every piece of knowledge gets a unique ID at
ingestion. It is recall, not a search. You get the exact content you
stored — verbatim, with attribution, in milliseconds.
The result: 97% reduction in tokens sent to the LLM.
Key differences from Mem0/Zep/Letta:
- No vectors, no embeddings, no similarity search
- Exact recall, not approximate
- Full audit trail with source attribution
- 100% local, AES-256 encrypted, zero data egress
Works with Claude Code, Cursor, any MCP client. Multi-agent memory sharing built
in.
GitHub: https://github.com/solonai-com/grantai