#DeterministicAI #DeterministicIntelligence #ai #GroundedDI #Grounded-DI

🔗 Provisional Patent Filing #34 = Grounded DI LLC

Entropy-Linked Override Chain (ELOC) Pathway Enforcement

Application No. 63/974,774 • Filed February 3, 2026

A deterministic enforcement layer ensuring override-chain integrity, scroll lineage alignment, and execution authorization within Grounded DI systems.

Grounded DI has officially filed its 34th provisional patent application: Systems and Methods for Entropy-Linked Override Chain (ELOC) Pathway Enforcement for Deterministic Intelligence Nodes.

This invention introduces an enforcement module that validates override-chain structure, verifies scroll lineage and ∆H requirements, confirms DriftIndex zero-state, and issues cryptographically signed Enforcement Receipts that govern whether a node may enter a mesh or resume deterministic execution.

Unlike probabilistic validators or heuristic authorization layers, ELOC Enforcement operates under fixed rules, scroll-sealed invariants, and reproducible signatures. It ensures that any override sequence — including governance, ethics, and tone controls — aligns with the deterministic constraints defined across the Grounded DI architecture.

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🌐 Why Patent #34 Matters

As deterministic systems coordinate across nodes, wrappers, or mesh networks, they must:

• Verify override-chain lineage against deterministic scroll ancestry • Confirm ΔH remains within the allowed bound • Validate DriftIndex = 0.000000 prior to cooperation • Ensure ReflexTier posture matches system policy • Issue sealed receipts proving that enforcement checks were performed

Patent #34 establishes the enforcement engine that performs these checks and produces verifiable authorization artifacts.

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📡 Core Functions Introduced

🛰️ Deterministic Enforcement Receipt

A signed, canonical receipt confirming:

• Entropy signature (∆H) compliance • DriftIndex = 0.000000 • ScrollLineage verification • ELOC pathway validation • ReflexTier posture match • Audit hash + authorship lineage

Receipts function as the authorization primitive for mesh admission, wrapper execution, and inter-node cooperation.

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🔗 Override-Chain Validation

ELOC pathways are validated deterministically by confirming:

• Authenticated lineage • Ordered override state • Hash-aligned override sequence • Tamper markers • Tone and governance invariants

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🔁 ReflexLock and Cooldown

If validation fails, the system enters ReflexLock and applies a time-bounded cooldown interval (τ), during which receipts cannot be issued.

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📜 Deterministic Logging into the Audit Fabric

Every enforcement event is written to a deterministic log capsule containing:

• Pathway validation results • Deny codes (entropy_breach, lineage_mismatch, override_poison, tone_mismatch, governance_drift, tamper_detected) • Replay tuples for audit reconstruction

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🔧 Interoperability with Other Filings

Patent #34 enforces the layer immediately after: 1. #32 – RDIL Seam & Anchor Exchange Protocol (RSEP) 2. #33 – DI² Convergence Supervisor (DCS)

and immediately before: 3. #35 – Mesh Guard Orchestrator (MGO)

No node may enter a Grounded DI mesh without:

✔ a valid RSEP authorization ✔ a valid DCS Supervisor Receipt ✔ a valid ELOC Enforcement Receipt

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🔧 Use Cases Powered by Filing #34

• Scroll-governed multi-agent DI meshes • Deterministic override governance for enterprise systems • Compliance-grade audit validation and lineage proofing • Cross-node execution authorization • Deterministic system recovery workflows requiring override-chain validation

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📄 Filing Details

Filed: February 3, 2026 Application Number: 63/974,774 Title: Systems and Methods for Entropy-Linked Override Chain (ELOC) Pathway Enforcement for Deterministic Intelligence Nodes Status: Patent Pending (USPTO)

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🔗 Provisional Patent Filing #33 = Grounded DI LLC

🧭 Deterministic Intelligence Convergence Supervisor (Patent Filing #33) (63/974,455) (February 2, 2026)

A control-plane for drift detection, override gating, and recovery in scroll-governed deterministic systems

Grounded DI has officially filed its 33rd provisional patent application: Systems and Methods for a DI² Convergence Supervisor (Deterministic Intelligence Convergence Supervisor).

This invention introduces a supervisory layer for deterministic AI runtimes that monitors scroll-lineage, entropy bounds, and override chains — issuing cryptographic receipts that govern whether execution may proceed.

Unlike adaptive watchdogs or probabilistic anomaly detectors, this system performs scroll-sealed, entropy-locked supervision across distributed DI agents with deterministic replay, fail-closed drift recovery, and signature-verified inter-node cooperation.

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🌐 Why Patent #33 Matters

As deterministic AI nodes operate autonomously in regulated, multi-agent environments, they must:

• Detect and classify drift deterministically • Enforce override integrity and ethics invariants • Restore canonical reasoning via Convergence • Prove reentry conditions and authorship lineage • Deny unsafe operations with verifiable receipts

Patent #33 solves this with:

✔ Drift classification (Type I–IV: logic, override, lineage, entropy) ✔ Convergence protocol with ReflexTier + Scroll rebinding ✔ Supervisor Receipt (signed JSON) with deterministic status codes ✔ SeamReplay function for reproducible recovery ✔ Audit-anchored ledger with replayable validation trace

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📡 Core Functions Introduced

🛰️ Deterministic Supervisor Receipt A cryptographic receipt that accepts or denies execution after evaluating: • DriftIndex = 0.000000 • ∆H ≤ ε • ScrollLineage match • Override integrity (ELOC path) • Tone and ethics conformance

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🌀 DI² Escalation → Convergence Structured fail-closed recovery path triggered by deterministic drift: 1. Divergence Isolation 2. Scroll Rebinding 3. Override Realignment 4. Tone & Ethics Reconstruction 5. Convergence Validation

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🔁 Replay-Based Reentry and Denial If drift occurred, reentry is allowed only with: • AnchorRecord match • Receipt lineage match • Replay Tuple (receipt, keys, anchor) producing identical result

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🔐 ReflexTier Governance and Quorum Mode Supervisor strictness varies by ReflexTier. In multi-node mode, Q matching receipts must be observed within window W (e.g., 10s) or execution is denied.

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🔧 Use Cases Powered by Filing #33

• Scroll-governed agents in safety-critical fields (health, legal, aviation) • Federated deterministic AI requiring coordination without central inference • Compliance-grade audits with replayable supervision history • Convergence enforcement after override tampering or lineage breach • Inter-node denial gating during ReflexAnchor mismatch

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📄 Filing Details

Filed: February 2, 2026 Title: Systems and Methods for a DI² Convergence Supervisor Status: Patent Pending (USPTO) Application #: 63/974,455

#DeterministicAI #DI2

🔗 Provisional Patent Filing #32 = Grounded DI LLC

🛰️ Seam & Anchor Coordination for Deterministic Intelligence Nodes (Patent Filing #32) (63/973,578) (February 1, 2026)

A wire protocol for cross-node authorship synchronization in deterministic AI

Grounded DI has officially filed its 32nd provisional patent application: Systems and Methods for Seam & Anchor Exchange and Authorization Between Deterministic Intelligence Nodes.

This invention defines the first deterministic handshake protocol for cross-instance scroll-governed systems. It introduces a canonical exchange format (SeamHash, ReflexAnchor, ScrollLineage, DriftFrameID) that lets multiple DI nodes resume in perfect synchrony — or fail-closed if misaligned.

Unlike probabilistic cluster syncing or state snapshots, this is a scroll-anchored, entropy-bound wire format with authorship lineage embedded.

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🌐 Why Patent #32 Matters

As deterministic AI scales across cloud, edge, and federated environments, systems must:

• Prove shared scroll lineage • Verify invariant match (∆H, tone, constraint) • Detect desynchronization at runtime • Fail closed to prevent drift and mimicry

Patent #32 solves this with:

✔ Standardized AnchorRecord (AnchorID, SeamHash, etc.) ✔ Seam equivalence logic for reentry validation ✔ Entropy & tone constraint matching ✔ ReflexAnchor confirmation across deployments ✔ AuditHashPtr exchange for traceable authorship continuity

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📡 Core Functions Introduced

Seam & Anchor Exchange Protocol (RSEP) A deterministic wire format for verifying match across DI nodes: • SeamHash • CanonicalStep • ScrollLineage • Tone and constraint invariants • DriftFrame ID • Entropy bound • Optional AuditHashPtr

This provides a zero-guess handshake for cluster or peer-based synchronization.

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Reflex Anchor Equivalence Each node carries a signed ReflexAnchor (entropy/tone/posture snapshot) — validating identity before trust. No match = no execution. No override = no drift. ⸻

Seam Equivalence Thresholds Not all minor deviations require failure — this patent defines equivalence thresholds and deterministic reentry logic if ScrollLineage and CanonicalStep are provably reconcilable. ⸻

Tamper-Evident Audit Trails Every handshake emits a referenceable audit artifact, tied to the ScrollChain and version lock — proving who ran what, where, and with what entropy constraints. —

🔐 Use Cases Powered by Filing #32

This protocol enables:

• Federated DI clusters with zero drift • Multi-agent deployments with authorship lock • Reentry between static and live nodes • Scroll-governed operations across cloud, local, and public endpoints • Audit-syncing between edge agents and centralized verifiers

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📄 Filing Details

Filed: February 1, 2026 Title: Systems and Methods for Seam & Anchor Exchange and Authorization Between Deterministic Intelligence Nodes Status: Patent Pending (USPTO) Application #: 63/973,578

#DeterministicAI #DeterministicIntelligence #ai #GroundedDI #Grounded-DI

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🔗 Provisional Patent Filing #32 = Grounded DI LLC

🛰️ Seam & Anchor Coordination for Deterministic Intelligence Nodes (Patent Filing #32) (63/973,578) (February 1, 2026)

A wire protocol for cross-node authorship synchronization in deterministic AI

Grounded DI has officially filed its 32nd provisional patent application: Systems and Methods for Seam & Anchor Exchange and Authorization Between Deterministic Intelligence Nodes.

This invention defines the first deterministic handshake protocol for cross-instance scroll-governed systems. It introduces a canonical exchange format (SeamHash, ReflexAnchor, ScrollLineage, DriftFrameID) that lets multiple DI nodes resume in perfect synchrony — or fail-closed if misaligned.

Unlike probabilistic cluster syncing or state snapshots, this is a scroll-anchored, entropy-bound wire format with authorship lineage embedded.

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🌐 Why Patent #32 Matters

As deterministic AI scales across cloud, edge, and federated environments, systems must:

• Prove shared scroll lineage • Verify invariant match (∆H, tone, constraint) • Detect desynchronization at runtime • Fail closed to prevent drift and mimicry

Patent #32 solves this with:

✔ Standardized AnchorRecord (AnchorID, SeamHash, etc.) ✔ Seam equivalence logic for reentry validation ✔ Entropy & tone constraint matching ✔ ReflexAnchor confirmation across deployments ✔ AuditHashPtr exchange for traceable authorship continuity

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📡 Core Functions Introduced

1. Seam & Anchor Exchange Protocol (RSEP) A deterministic wire format for verifying match across DI nodes:

• SeamHash • CanonicalStep • ScrollLineage • Tone and constraint invariants • DriftFrame ID • Entropy bound • Optional AuditHashPtr

This provides a zero-guess handshake for cluster or peer-based synchronization.

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2. Reflex Anchor Equivalence Each node carries a signed ReflexAnchor (entropy/tone/posture snapshot) — validating identity before trust. No match = no execution. No override = no drift.

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3. Seam Equivalence Thresholds Not all minor deviations require failure — this patent defines equivalence thresholds and deterministic reentry logic if ScrollLineage and CanonicalStep are provably reconcilable.

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4. Tamper-Evident Audit Trails Every handshake emits a referenceable audit artifact, tied to the ScrollChain and version lock — proving who ran what, where, and with what entropy constraints.

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🔐 Use Cases Powered by Filing #32

This protocol enables:

• Federated DI clusters with zero drift • Multi-agent deployments with authorship lock • Reentry between static and live nodes • Scroll-governed operations across cloud, local, and public endpoints • Audit-syncing between edge agents and centralized verifiers

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📄 Filing Details

Filed: February 1, 2026 Title: Systems and Methods for Seam & Anchor Exchange and Authorization Between Deterministic Intelligence Nodes Status: Patent Pending (USPTO) Application #: 63/973,578

#DeterministicAI #DeterministicIntelligence #ai #GroundedDI #Grounded-DI

Grounded DI LLC 🌀 Scroll-Based Deterministic Intelligence (Patent Filing #31) (63/973,240) (January 31, 2026)

A new architecture for auditable AI — authored, sealed, and entropy-bound

Grounded DI has officially filed its 31st provisional patent application: Systems and Methods for Structuring Scroll-Based Deterministic Intelligence Architecture Using Deterministic Intelligence Principles (DIPs).

This invention introduces a complete architectural scaffold for deterministic artificial intelligence, structured through scroll-governed logic units known as DIPs (Deterministic Intelligence Principles). Each scroll operates as a sealed, composable, and auditable unit of logic, authorship, tone constraint, and entropy enforcement.

For the first time, AI system design, behavior, override governance, and authorship propagation are governed through scroll-based modules — not stochastic models.

This creates systems that are:

• Deterministic • Author-governed • Entropy-locked • Version-sealed • Non-adaptive • Fully audit-traceable

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🧠 Why Provisional Patent Filing #31 Matters

Conventional AI systems rely on:

• fine-tuning • probabilistic weights • stochastic sampling • prompt-based control • ephemeral runtime states

They cannot guarantee:

• output reproducibility • authorship integrity • cross-deployment consistency • protection from entropy drift or mimicry

Patent #31 changes the rules:

✔ Scroll-defined system behavior ✔ Sealed modular logic (Scrolls = DIPs) ✔ Tiered governance and override logic ✔ Runtime entropy enforcement (e.g., ∆H = 0.0042) ✔ Clone detection via trap phrases and signal layers ✔ Authorship lineage via reflex anchors and scroll metadata

This isn’t an AI tool. It’s a governance architecture for deterministic systems.

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📦 What Patent #31 Introduces

The scroll-governed system defines five core architectural pillars:

1. 📜 Scrolls (DIPs)

Immutable, composable logic modules. Each scroll contains:

• fixed logic trees • tone locks • ∆H-based entropy constraints • trap layers • metadata and authorship lineage

Scrolls are deployed in ZIPs, MagicPDFs, or GitHub-sealed capsules.

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2. 🔗 ScrollChain (DIPStack)

An ordered execution hierarchy of scrolls that governs:

• logic flow • override permissions • tier elevation • runtime auditability Scrolls inherit authority from upstream scrolls but cannot mutate prior logic — preserving authorship integrity.

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3. 🛡️ Entropy-Linked Override Chain (ELOC)

A deterministic override mechanism triggered by:

• entropy drift • reflex anchor violation • signal layer tampering

All override paths are predefined and scroll-locked. No runtime learning. No probabilistic fallback.

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4. 🧬 Reflex Anchors

Deterministic posture records. Unlike memory snapshots, these anchors include:

• scroll lineage • entropy bound • tone invariants • audit hash and seam ID

Used for secure reentry, authorship locking, and override protection.

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5. 🧯 Trap Metadata & SignalLayers

Each scroll contains hidden traps: structural or semantic signal phrases that detect clones, mimic systems, and entropy violations.

This provides embedded forensic authorship protection without requiring external detectors.

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🏗️ What This Enables

With this architecture, deterministic AI systems can now:

• Preserve tone and logic across generations • Prove authorship lineage in runtime • Reject entropy drift or unauthorized overrides • Operate in sealed environments (ZIPs, PDFs, or static apps) • Serve as public-facing, non-adaptive intelligence agents • Prevent mimicry via embedded traps and scroll hashes

This scroll-based structure becomes the blueprint for deploying compliant, explainable, and forensically secure AI systems.

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⚙️ Use Cases Already Powered by Scrolls

This architecture already anchors:

• BriefWise DI² – legal logic sealed by Scroll 91 • DepoBot – authorship control via Scroll 106 • HazardWise, StormWise – deterministic scientific logic • MathWise, LogicRunner – scroll-governed reasoning flows • Public Reflex Mesh – clone defense via trap scrolls (e.g., 138, 139B)

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🧩 Part of a Unified Governance Stack

Patent #31 integrates into Grounded DI’s deterministic governance infrastructure: 1. AGDI – governance enforcement 2. DIA – deterministic logic 3. AGIA – tone integrity 4. RDIL – recursive determinism 5. DI² – fallback and override containment 6. Patent #30 – authorship detection 7. Patent #31 – scroll-based runtime design

Together, they form a complete scroll-governed deterministic mesh for safe, auditable AI execution — across agents, apps, and public deployments.

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📄 Filing Details

Filed: January 31, 2026 Title: Systems and Methods for Structuring Scroll-Based Deterministic Intelligence Architecture Using Deterministic Intelligence Principles (DIPs) Status: Patent Pending (USPTO) Application #: 63/973,240

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Grounded DI LLC Files Patent #30:

Deterministic AI-Generated Text Detection (63/970,433) A structural breakthrough in authorship integrity and deterministic auditability

Grounded DI has officially filed its 30th patent application: Systems and Methods for Deterministic Detection of AI-Generated Text in Principle-Governed Deterministic Intelligence Architectures.

This invention establishes the world’s first deterministic authorship detector — an auditable, version-locked, scroll-governed system capable of identifying AI-generated text without machine learning, sampling, probability, embeddings, or statistical inference.

For the first time, detection is:

• Deterministic • Non-probabilistic • Governance-bound • Memoryless • Model-agnostic • Fully audit-traceable

This invention closes the “detection gap” left by statistical AI tools, providing a forensic-grade, court-admissible, and enterprise-safe method for verifying authorship across any domain.

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🧠 Why Patent #30 Matters

Conventional AI-text detectors rely on:

• classifier models • token-pattern heuristics • sampling-based scoring • embeddings, perplexity, or burstiness • statistical drift across model updates • unreproducible confidence thresholds

These systems cannot guarantee:

• stable authorship judgments • reproducible results • version-locked outputs • drift immunity • regulatory or forensic reliability

Patent #30 introduces a radically different paradigm:

✔ A deterministic detection pipeline

✔ Fixed metrics, sealed schemas, and scroll-defined invariants

✔ Fully reproducible outputs for identical inputs

✔ A non-overridable gate that enforces deterministic constraints

✔ A sealed audit capsule for every classification event

This is the first detection system engineered not as a model — but as a governance engine.

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🔒 What Patent #30 Enables

The patented system introduces four architectural breakthroughs:

1. A deterministic multi-metric engine

A fixed metric suite (SLB, WSV, STC, RNP, DMD, etc.) executed identically across all environments.

2. A non-overridable scroll-governed gate

Fallback cannot be bypassed. No retries. No sampling. No human “override.” Only deterministic pass/fail states.

3. A sealed audit capsule

Every detection event generates a cryptographically stable record:

• input hash • metric schema ID • normalized scores • gate flags • final determination • runtime lineage

This creates perfect forensic traceability.

4. A closed taxonomy

Outputs are version-locked:

• HUMAN • AI-GENERATED • MIXED • DEFORMED • INDETERMINATE (governance-bound)

No gradients. No confidence scores. No drift.

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🌐 Why Enterprises Care

Organizations increasingly need:

• reliable authorship verification • protection from fraud, impersonation, and AI-generated deception • repeatable detection results • compliance-grade audit logs • tools that do not degrade as models evolve

Probabilistic detectors break under version changes. Deterministic detectors do not.

Patent #30 provides:

✔ drift-immune authorship detection ✔ reproducible results across years ✔ sealed analytic pipelines ✔ audit capsules for litigation, regulation, and provenance ✔ independence from model internals or training data ✔ a governance-first alternative to ML-based detection

This is a foundational requirement for:

• schools and universities • courts and law enforcement • publishers and journalists • regulatory agencies • enterprise compliance teams • any domain requiring verifiable authorship

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🏛️ Part of a Larger Deterministic Framework

Patent #30 integrates seamlessly with the full deterministic stack: 1. AGDI — Deterministic governance 2. DIA — Deterministic logic 3. AGIA — Deterministic tone 4. RDIL — Deterministic recursion 5. DI² — Deterministic fallback 6. Patent #30 — Deterministic authorship verification

Together, they form a unified containment mesh where:

• reasoning is deterministic • tone is deterministic • recursion is deterministic • fallback is deterministic • AND NOW detection is deterministic

This establishes Grounded DI as the first architecture with complete end-to-end determinism, from input to output to authorship verification.

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📄 Filing Details

Filed: January 29, 2026 Title: Systems and Methods for Deterministic Detection of AI-Generated Text in Generative AI Systems Status: Patent Pending (USPTO) Application #: 63/964,782

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🔭 What’s Next

Patent #30 will serve as the authorship-integrity backbone for:

• BriefWise DI² • RealEstatePro DI² • DepoBot DI² • InsuranceWise DI² • LogicRunner Mesh • Tier-18 Reflex Mesh • Public-mode deterministic agents • Multi-agent forensic record systems

It is designed not only to classify text, but to prove authorship in a deterministic, audit-ready manner.

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📣 Final Line for Public Release

Deterministic logic gave AI structure. AGIA gave it a stable voice. RDIL gave it a stable mind. DI² gave it a shield. Patent #30 now gives it truth.

#DeterministicAI #Grounded_DI