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Arachnet™
Distributed Sensing & Resonance Mesh Layer — coordinated anomaly detection across digital and physical environments.
Arachnet is the “nervous system” mesh of the Ascend Dynamix ecosystem — a distributed layer that correlates signals,
detects drift, and coordinates response across nodes without forcing a brittle, centralized control point.
At a Glance
Filing: U.S. Provisional (Application No. 63/918,438) |
Filed: November 16, 2025 |
Inventor: Gareth Karpel
- What it is: A distributed sensing and resonance mesh for real-time anomaly detection.
- What it correlates: cryptographic signals, behavioral drift, tension shifts, and physical event-fields.
- What it enables: coherent cross-node awareness and coordinated response without single-point fragility.
Why Arachnet Exists
Modern systems fail quietly: logs fragment, signals stay siloed, and anomalies appear “normal” when viewed in isolation.
Traditional monitoring often becomes centralized, reactive, and overwhelmed — producing noise rather than insight.
Arachnet is designed to restore coherence: it treats the environment as a field of signals and learns what “stable” looks like,
so drift becomes detectable early and response can be coordinated calmly and deterministically.
What Arachnet Is
Arachnet is a multi-node mesh layer that listens to distributed signals and generates a higher-order interpretation of system health.
It is designed to operate across:
Domains of Observation
- Digital signals: session events, authentication integrity, policy outcomes, cryptographic lifecycle signals.
- Behavioral signals: deviation from expected interaction patterns and trust posture baselines.
- Physical signals: integration inputs such as AetherScale™ event-fields (thermal/load shifts).
- Mesh signals: cross-node resonance patterns that reveal distributed anomalies.
Core Innovations
1) Resonance-Based Correlation
Arachnet is structured to correlate patterns across nodes — not merely aggregate logs. It looks for resonance across signals:
repeated motifs, synchronized drift, and field-level changes that become meaningful only when combined.
2) Distributed Detection Without a Single Controller
The mesh is designed to reduce reliance on a centralized “brain.” Nodes can generate local interpretations and
share constrained summaries, enabling resilience and graceful degradation under stress.
3) Cross-Layer Compatibility
Arachnet is designed to accept signals from cryptographic layers (e.g., SAFE Engine events), platform layers (AetherGuard),
and physical layers (AetherScale). This enables unified awareness across what’s happening and what it means.
4) Coercion-Aware & Integrity-Aware Routing
The mesh can support sovereignty-first scenarios by distinguishing normal access from coercion patterns and by
tracking integrity events without escalating into fear-based automation. The goal is calm detection + controlled response.
5) Field-Level Outputs
Instead of “alerts only,” Arachnet is designed to produce interpretable outputs: drift scores, anomaly fields,
and node-level confidence that higher layers can use for policy decisions and safe response.
Example Use Cases
- Endpoint ecosystems: detect coordinated drift across devices, accounts, or trust postures.
- Secure environments: correlate cryptographic session events with environmental change signals.
- Enterprise + home: unify integrity and behavior awareness into a single calm operational view.
- Distributed nodes: mesh-based health scoring and anomaly coordination across a fleet.
How It Fits the Ecosystem
Arachnet connects the Ascend Dynamix layers into one coherent organism:
- SAFE Engine: contributes cryptographic lifecycle and session integrity signals.
- AetherGuard™ BioCore: contributes runtime integrity and policy-control signals.
- AetherScale™: contributes physical event-fields for environmental awareness.
- AetherPulse™ ZTMN: can contribute signal-level trust posture in mobility contexts.
IP & Disclosure Note
This page is a public executive summary intended to describe the technology at a high level.
It does not disclose filing text, claims, or implementation details. Additional materials may be made
available for diligence and review upon request.