Phocoustic Patent Portfolio — Interlocking Architecture

A Unified, Physics-Anchored Intellectual Property Platform

Phocoustic’s 20-patent family forms a stacked, mutually dependent architecture in which each layer reinforces the one below it.
Together, they create a defensible end-to-end pipeline from sensor input → physics drift extraction → semantic development → cognitive stability → cross-object lineage.

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1. SENSOR & PHYSICS LAYER (Foundational IP)

Goal: Extract real, physically admissible drift from light/structured-light/acoustic signals.

Core patents:

• PASDE – Physics-Anchored Structured Drift Extraction

• PADR – Drift persistence & multi-frame admissibility

• SOEC – Temporal stability & evidence control

• PEQM – Physical continuity & material plausibility

• SCVL / Q-SCVL – Classical & quantum-origin self-consistency

• VISURA – Multimodal acquisition layer

Function:
This layer prevents hallucination, noise, glare artifacts, or statistical drift.
It forms the base of every downstream semantic or cognitive capability.

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2. DRIFT STRUCTURING & REFERENCE LAYER

Goal: Convert raw drift into structured, traceable, stable representations.

Core patents:

• PQRC / SPQRC – Pattern-Quantized Ranking Codes

• DDAR / R-PADE – Dynamic, physics-validated rolling reference

• SGB – Immutable static golden baseline

• RMS – Deterministic reference-mode selection

• RFE – Fusion of static + dynamic references

Function:
These patents define how the system forms stable, non-corruptible internal references —
a foundational requirement for inspection, navigation, and semantic reasoning.

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3. GEOMETRY, SEMANTIC & STRUCTURED-LIGHT LAYER

Goal: Translate drift and geometry into meaningful physical interpretations.

Core patents:

• QLSR – Quantum-Linked Structured-Light Semantic Recall

• SLDI – Structured-Light Drift Invariants

• PSYM – Physics-Structured Semantic Mapping

• PAIL – Physics-Anchored Intent Layer (semantic gating)

Function:
This layer enables PCB/wafer defect detection, fine geometric analysis, fog/glare navigation,
and drift-based semantic overlays — all without AI training or neural networks.

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4. SEMANTIC DEVELOPMENT LAYER (CIP-12)

Goal: Enable physics-anchored formation, maturation, and pruning of semantic structures.

Core patents:

• PHOENIX – Developmental semantic engine

• PAMF – Physics-Anchored Meaning Formation

• SGN – Semantic Genome (stable semantic memory)

Function:
These filings establish deterministic rules governing how meaning forms from drift —
a significant differentiator from trained statistical systems.

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5. SEMANTIC EPIGENETICS LAYER (CIP-13)

Goal: Allow environment-conditioned shaping of semantic development without training.

Core patents:

• SEGEN – Semantic Epigenetics Generator

• EIC – Environmental Influence Channels

• SEC / EPC – Exposure and pulse-conditioning formulas

• SGN-E – Epigenetic overlays on semantic genome

Function:
This layer introduces domain specialization (PCB vs wafer vs fog vs robotics),
semantic reinforcement or suppression, and explainable developmental pathways.
It is unique, foundational ACI technology.

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6. OBJECT CONTEXT & LINEAGE LAYER

Goal: Bind drift, meaning, and epigenetics to individual physical objects.

Core patents:

• OCID – Object Context Identification

• ORDL – Object-Resolved Drift Lineage

• Cross-object semantic lineage integration with SGN/PHOENIX/SEGEN

Function:
Essential for PCB lines, conveyors, wafer lots, robotics, and manufacturing auditability.
A major competitive barrier — competitors cannot emulate this without infringement.

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7. SYSTEM-LEVEL ACI LAYER (CIP-10 & ACI Track)

Goal: Govern the entire pipeline using physics-only logic to prevent hallucination.

Core patents:

• VGER – Vector-Governed Epigenetic Reasoner

• PA-CI – Physics-Anchored Cognitive Intelligence

• M-PACF / M-CAPF – Multi-channel anchored cognitive frameworks

Function:
These filings establish a safe, physics-grounded cognitive layer
that never escapes drift evidence and never enters statistical hallucination.

PORTFOLIO INTERLOCK — The Big Picture

[SENSORS]
   ↓ VISURA
[PHYSICS DRIFT ENGINE]
   PASDE → PADR → SOEC → PEQM → SCVL
   ↓
[REFERENCE FORMATION]
   SGB ↔ DDAR/R-PADE → RFE → RMS
   ↓
[DRIFT STRUCTURING]
   PQRC/SPQRC → QLSR/SLDI
   ↓
[SEMANTIC LAYER]
   PSYM → PAIL → PHOENIX → PAMF → SGN
   ↓
[EPIGENETICS]
   SEGEN → EIC → SEC/EPC → SGN-E
   ↓
[OBJECT LINEAGE]
   OCID → ORDL → SGN lineage binding
   ↓
[ACI SUPERVISION]
   VGER → PA-CI → M-CAPF

..........................

Patent Filings, continued

This page provides high-level summaries of selected U.S. and international patent filings related to the VisualAcoustic Semantic Drift Engine (VASDE) and the broader Phocoustic platform. These summaries are intended for general informational and investor-relations purposes only.

For legal questions regarding the scope of protection, please consult qualified patent counsel and the underlying published applications.

Press Release — International Patent Application for VASDE

Phocoustic, Inc. Files PCT Application for VisualAcoustic Semantic Drift Engine (VASDE)

November 2025 — Champaign, Illinois — Phocoustic, Inc. has filed an international Patent Cooperation Treaty (PCT) application covering its VisualAcoustic Semantic Drift Engine (VASDE). The filing extends the company’s earlier U.S. patent family and seeks worldwide priority for its physics-informed approach to anomaly detection and semantic drift classification.

At a high level, the PCT consolidates innovations in:

• Quantized Audio-Inferred Representation (QAIR) — structured encoding of multi-spectral measurements into an acoustic-like domain.
• Physics-Anchored Drift Reduction (PADR) — methods for emphasizing physically meaningful drift while suppressing unstable variation.
• Pattern-Quantized Ranking Codes (PQRC) — pattern-encoded drift signatures that support explainable ranking and localization.

The PCT also references additional modules (e.g., QLSR, PSSS, CAF) as part of an integrated physics-anchored framework. Detailed algorithms and claim boundaries are contained in the PCT specification and related U.S. continuation-in-part filings, not on this website.

CIP-13: Object-Resolved Drift Lineage & Semantic Epigenetics

CIP-13 (described more fully on our home page) builds on earlier filings to introduce:

• Object Context Identification (OCID) — associating drift history with individual objects in production and sequential-inspection flows.
• Object-Resolved Drift Lineage (ORDL) — tracking how anomalies evolve for each object over time.
• Semantic Epigenetics (SEGEN) — mechanisms by which environmental conditions influence physics-anchored semantic development.

CIP-13 is designed to strengthen auditability, traceability, and environmental conditioning in physics-anchored cognitive systems. Implementation specifics appear in the CIP-13 patent documents.

Press Release — CIP-11

Classical Physics–Anchored Drift Benchmarking and Stability Architecture

Phocoustic, Inc. has filed CIP-11, titled “System and Method for Classical Physics-Anchored Drift Benchmarking, Quantum-Conditioned Measurement Clarification, and Assistive Human-Geometry Detection.”

CIP-11 extends the VisualAcoustic platform with a framework for comparing physics-anchored drift against conventional machine-learning outputs, and for structuring stability references across both static and dynamic environments. The filing:

• Defines a benchmark layer for comparing physics-derived drift metrics to CNN/PINN-based indicators under challenging conditions such as fog, glare, and motion.
• Introduces a two-tier stability architecture combining static and adaptive references (e.g., a “golden baseline” and an updated drift reference) under physics-informed admissibility rules.
• Clarifies how quantum-origin physical measurements (e.g., Raman or vibrational signatures) may be used as classical stabilizing channels, without quantum computing.
• Describes assistive human-geometry detection in visibility-degraded environments, using physically derived geometry cues without biometric identification.

Technical details, gating mechanisms, and data-structure implementations are defined in the CIP-11 specification and associated claims.

CIP-11 also harmonizes earlier drift demonstrations, visibility-degraded examples, and PCB / wafer benchmarks with the broader VASDE portfolio, helping preserve priority for previously demonstrated behaviors.

A Classical-Only, Low-Compute Alternative

CIP-11 reinforces Phocoustic’s focus on classical, training-minimized, and explainability-oriented architectures. In general terms, the system is designed to:

• Operate without mandatory neural-network training steps.
• Provide deterministic, regulator-friendly outputs where possible.
• Reduce the likelihood of unstable or hard-to-explain behavior often associated with unconstrained AI models.
• Support deployment on CPUs, edge devices, and embedded platforms.

These descriptions are conceptual only; specific method claims are found in the CIP-11 application.

CIP-10: Predictive Drift Reasoning & Multi-Camera Cognitive Fusion

CIP-10 advances the VisualAcoustic platform beyond pure anomaly detection into predictive and goal-aligned reasoning built on physics-anchored drift evidence.

Building on the dual-domain architecture introduced in earlier filings, CIP-10 describes a system that can:

• Forecast likely evolution of drift patterns under defined physical constraints.
• Align predicted drift with operator-defined regions of risk or interest.
• Fuse multiple VISURA camera views into a unified interpretation with explicit consistency checks.
• Use textual or symbolic cues in the environment as evidence-backed risk anchors.
• Constrain higher-level inferences to drift that passes physics-based admissibility rules.

CIP-10 introduces families of concepts such as predictive drift fields and semantic risk manifolds, but the exact mathematics, thresholds, and data structures are specified only in the patent application itself.

Application examples include semiconductor manufacturing, PCB and microelectronics inspection, industrial robotics, visibility-degraded navigation, and structural monitoring.

CIP-10 ACI: Physics-Bound Cognitive Intelligence

CIP-10 ACI describes a Physics-Anchored Conscious / Cognitive Intelligence (PA-CI) layer built entirely in the classical domain. It formalizes how drift-based evidence can be promoted into stable cognitive states under multiple, overlapping governance loops.

At a high level, the filing:

• Defines a Conscious Coherence Envelope (CCE) that determines when drift is persistent, resonance-aligned, and admissible for semantic activation.
• Extends CCE with quantum-conditioned classical measurements (such as Raman or fluorescence measurements) to form QCCE, expanding the available evidence without introducing quantum computing.
• Introduces a PA-CI supervisory layer that only activates when several independent stability checks agree, helping to avoid premature or unsupported interpretations.
• Describes self-consistency verification loops (SCVL / Q-SCVL) that check multi-module outputs for contradictions and can halt cognition when inconsistencies appear.
• Outlines additional structures (e.g., PERC, QDP, QASI, PEQ-AGI) that expand classical drift governance and evidence-qualified reasoning.

In general, CIP-10 ACI is aimed at creating physics-constrained, self-verifying cognitive behavior rather than free-form, purely statistical “AGI.” All detailed mechanisms are captured in the CIP-10 ACI claims and specification.

CIP-9: Multi-Camera Drift Consensus & Semantic Governance

CIP-9 focuses on multi-camera, physics-governed semantic consensus. It introduces mechanisms by which multiple VISURA viewpo