SuperLocalMemory V4.1.9

Rent the LLM. Own the memory.

Rent an LLM — but own the memory, for your company and for your industry.

The governed memory layer for AI agents: local-first, auditable, and built for the compliance obligations teams now actually carry.
Models are interchangeable and rented by the token. What your agents remember is yours — it is your customers' data, your retention obligations, and your audit trail. SLM keeps that layer on infrastructure you control, with multi-workspace isolation, role-based access, and GDPR + EU AI Act governance controls built in.

The boundary. SuperLocalMemory starts with a local runtime; provider-backed enrichment, cloud backup, connectors, and proxy use are explicit choices. Different products solve different boundaries. Published benchmark evidence carried into V4 comes from the published V3 research architecture; it is not a claim of a newly rerun V4 package benchmark.

How to check that, rather than believe it. Every reliability guarantee here is stated as a falsifiable invariant, tested under an adversarial condition with a negative control, and shipped with the harness that regenerates the evidence: python benchmark/run_all.py --trials 200 --output-dir results/. What each experiment does not exercise is stated too.

v4.1.9 — one control plane: SLM-Mesh peer coordination · multi-scope memory (personal / shared / global) · profiles · Cache · Compress · 7-layer retrieval · code graph · Entity Explorer · skil