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