Transactional Neural Reasoning AI (TNRAI) Patent Application

ChangeBridge: Patent Apps - AI & Computing (G06N)

Published March 26th, 2026

Detected March 31st, 2026

Summary

USPTO published patent application US20260087387A1 for Transactional Neural Reasoning AI (TNRAI), a novel AI system designed for complex decision-making. The application describes a five-pillar architecture including delta-path modeling, skew-based adversarial recognition, vector memory recall, ambient reasoning overlays, and a multi-logic arbitration engine. Filed by inventor Joshua B. Williamson under application number 19171498.

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What changed

USPTO published patent application US20260087387A1 for Transactional Neural Reasoning AI (TNRAI), a novel AI system for complex decision-making. The application discloses a five-pillar architecture integrating delta-path modeling for real-time outcome deviation detection, skew-based adversarial recognition, vector memory recall for behavioral context, ambient reasoning overlays, and a multi-logic arbitration engine that fuses rule-based, statistical, situational, and historical reasoning. The system evolves via CI/CD feedback loops and supports conditional triggers based on logic patterns or confidence thresholds. CPC classifications include G06N 5/043 and G06F 8/71.\n\nThis publication is informational for compliance purposes; patent applications do not create immediate regulatory obligations. Technology companies developing AI systems for automation, compliance enforcement, customer engagement, or transaction-based control should review the disclosed architecture for potential licensing considerations or competitive awareness. No compliance deadlines or penalties are associated with this filing.

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Transactional Neural Reasoning AI (TNRAI)

Application US20260087387A1 Kind: A1 Mar 26, 2026

Inventors

Joshua B Williamson

Abstract

Transactional Neural Reasoning AI (TNRAI) is a novel class of artificial intelligence designed to simulate human-like reasoning during live, multimodal user sessions. TNRAI departs from traditional static inference models by integrating a five-pillar architecture: (1) delta-path modeling for real-time outcome deviation detection, (2) skew-based adversarial recognition, (3) vector memory recall for behavioral context, (4) ambient reasoning overlays to incorporate situational data, and (5) a multi-logic arbitration engine that fuses rule-based, statistical, situational, and historical reasoning. The system evolves continuously via a CI/CD feedback loop, adjusting its logic and thresholds based on live outcomes. TNRAI supports overlays such as time or location constraints to influence reasoning and can activate conditional triggers based on logic patterns or confidence thresholds. This architecture enables adaptive, deliberative decision-making in real time, extending the utility of AI across domains such as automation, compliance enforcement, customer engagement, and transaction-based system control.

CPC Classifications

G06N 5/043 G06F 8/71

Filing Date

2025-04-07

Application No.

19171498

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Named provisions

Delta-Path Modeling Skew-Based Adversarial Recognition Vector Memory Recall Ambient Reasoning Overlays Multi-Logic Arbitration Engine CI/CD Feedback Loop