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NARI Nano

Four-sphere expert cognition for edge systems.

NARI Nano is a compact expert reasoning brain for one bounded operational world. It does not try to be general. It learns the evidence, risks, rules, limits, and authority model of its domain, then produces auditable decisions and operator-safe proposals.

Nano stays small by narrowing its world: local evidence, clear limits, CPU-class deployment, and reviewable proposals before critical-system change.

Soft abstract geometric blocks representing compact Nano edge cognition

Pilot domain

Router cyber-defense

The current Nano-class pilot is training for an enterprise-grade router platform: router-only evidence, Suricata-rule proposals, no endpoint overclaiming, no direct mutation, and operator authority.

Deployment profile

Built for the edge

NARI Nano can reason inside a router, controller, device, or local appliance where GPU-class compute is unavailable, unwanted, or too expensive. Its strength is not open-ended language generation; its strength is efficient domain reasoning under strict safety boundaries.

Domain expansion

Many expert brains

The same architecture can be parented into expert systems for robotics, navigation, aviation support, industrial operations, medical devices, and infrastructure monitoring.

Fusion behavior

Small without reckless

If threat reasoning sees danger but evidence is incomplete, the gate can downgrade to inspect. If evidence is strong but action authority is missing, it produces an operator proposal instead of mutation.

What makes Nano different

Small enough for the edge. Structured enough to be trusted.

Nano does not use a transformer as the core mind.

Nano is built for local CPU-class inference, privacy, predictable latency, and hardware independence.

Nano separates Evidence, Pattern, Judgment, and Operational Self-Model spheres before the fusion gate produces final output.

Nano emits evidence, confidence, rationale, limits, and operator proposals instead of pretending uncertainty is certainty.

Nano preserves operator approval, rollback, audit, and policy boundaries before any critical-system change.

Nano can be trained through sealed schooling, shadow exams, redaction gates, and promotion reviews.