A unifying framework for cross-model AI memory
Neuro Cumulus frames advanced AI systems as a coordinated cloud of models and agents connected through a governed memory substrate. The core problem is not only prompt routing. It is semantic continuity across model families, modalities, tenants, permissions, and time.
Core layers
- I/O perimeter: typed requests, tools, files, and external systems.
- Short-term working state: thread-scoped context, checkpoints, and agent scratchpads.
- Long-term memory: semantic and episodic stores with provenance, confidence, and retention rules.
- Federated retrieval: permissioned memory lookup across local and remote stores.
- Governance controls: access policy, audit records, conflict handling, and consistency rules.
Evaluation questions
Teams evaluating this architecture should ask how memories are written, who can read them, how conflicts are resolved, what is retained, what is forgotten, and how source evidence is recovered when an agent makes a claim.