Kremis is an embedded graph store (Rust, Apache 2.0) built around one constraint: every answer must trace back to a real data point.

How it works: - You ingest your data as EAV signals (entity, attribute, value) - Kremis stores them in an append-only graph (redb underneath) - Every query returns one label: FACT — path exists in your graph INFERENCE — derived from graph traversal UNKNOWN — "not in your data, I won't guess"

The LLM never writes to the graph. Only your verified signals do. The graph can't hallucinate — it either has the path or it doesn't.

There's a runnable demo (Python stdlib, no pip): examples/demo_honesty.py It ingests 10 signals, asks 6 questions, shows which LLM answers are grounded and which are fabricated.

It also has an HTTP API and MCP support (Claude can query your graph directly via tool calls).

Honest limitation: ingestion is EAV format, so you need to reshape your data first. Working on making this easier.