SuperLocalMemory 4.0: The Governed Memory Operating System for AI Agents
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Abstract (arXiv)
We present SuperLocalMemory 4.0, a governed, local-first memory operating system for AI agents, unifying multi-channel retrieval under reciprocal-rank fusion, bi-temporal recall, multi-scope isolation, role-based access, verified erasure, and a hash-chained audit trail. A reliability spine governs the primary write path: generation-fenced admission, verifiable memory transactions with per-projection apply, verify, compensate and erase owners, and hash-checkable completion manifests. Eleven fault-injection scenarios, each repeated 200 times, upheld 2,199 of 2,200 scoped component properties. This version leads with a negative result. Ten mechanisms here were implemented, reachable on a live call path, and ineffective at their final connection. Implemented, reachable and effective are three different questions, and the third requires an oracle independent of the mechanism under test. We contribute two mechanical invariants that supply one: a prior-distance assertion over Bayesian learners, and a join-liveness assertion over schema-guarded paths that reports where a guard's missing data resides. A three-arm ablation varying only the recall session-identifier namespace moves no posterior with the defect present and every instantiated arm with it absent, while a negative control that writes every ticket but supplies no engagement settles nothing. We withdraw the previous version's governed write-envelope overhead figure: the two paths it differenced are not comparable. Timing the envelope in place gives an 11.0 ms governed write of which the envelope is 70.6 percent, but the generation fence costs 1.9 microseconds and the obligation ledger 42 microseconds. The cost is durability, not governance.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 18 of its 36 references that are in the map. First posted on arXiv 8 Aug 2026.
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18 of 36 references.
References · 18
- 2024Evaluating Very Long-Term Conversational Memory of LLM Agentscited by 800
- 2025Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memorycited by 722
- 2024LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive Memorycited by 656
- 2025From RAG to Memory: Non-Parametric Continual Learning for Large Language Modelscited by 223
- 2025LightMem: Lightweight and Efficient Memory-Augmented Generationcited by 163
- 2025MIRIX: Multi-Agent Memory System for LLM-Based Agentscited by 160
- 2025MemOS: A Memory OS for AI Systemcited by 129
- 2025TurboQuant: Online Vector Quantization with Near-optimal Distortion Ratecited by 116
- 2026MemoryArena: Benchmarking Agent Memory in Interdependent Multi-Session Agentic Taskscited by 72
- 2024QJL: 1-Bit Quantized JL Transform for KV Cache Quantization with Zero Overheadcited by 47
- 2024RaBitQ: Quantizing High-Dimensional Vectors with a Theoretical Error Bound for Approximate Nearest Neighbor Searchcited by 46
- 2026MemTX: Transactional Belief Commit for Stateful Agent Memorycited by 12
6 more
- 2026Governed Shared Memory for Multi-Agent LLM Systemscited by 8
- 2026Beyond Similarity: Trustworthy Memory Search for Personal AI Agentscited by 6
- 2026MemTxn: A Transaction Boundary for Source-Supported Updates and Complete-State Recovery in Agent Memorycited by 5
- 2026Governed Memory: A Production Architecture for Multi-Agent Workflowscited by 4
- 2026PROJECTMEM: A Local-First, Event-Sourced Memory and Judgment Layer for AI Coding Agentscited by 3
- 2026SF-AMS: Strategic Forgetting for Structured Memory in LLM Agentcited by 1
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Citing papers per year: 2026: 2.
2 papers.