Grounded DI LLC

📘 Provisional Patent Filing #41 – MathWise

Deterministic Mathematical Computation & Audit System Application No. 63/984,593 • Filed: February 17, 2026

⸻

🌐 Why Patent #41 Matters

Mathematics is the backbone of scientific modeling, financial systems, diagnostics, engineering, and safety-critical computation. But today it is executed through probabilistic models, unstable floating-point pipelines, and opaque, non-replayable heuristics.

MathWise changes all of that.

It is the first scroll-governed, fully deterministic mathematical computation engine, designed to produce identical, auditable, drift-free numerical results across: • scientific workflows • financial models • diagnostics & signal processing • engineering simulations • legal/forensic calculations • safety-regulated environments

MathWise enforces:

• 📜 Authorship-anchored numeric pipelines • 🔁 Replayable deterministic opcode paths (DOSI) • 🔐 Tamper-detectable computation (DriftFrame + ΔH gating) • 🧾 Immutable computation ledgers & property verifications • 🎯 Bounded-error, value-stable numerical transforms • 🧮 Machine-replayable proofs of equivalence (RPE)

With MathWise, numerical results become evidence-grade deterministic artifacts, not probabilistic outputs.

⸻

🧱 Core Components

✅ DOSI — Deterministic Opcode Sequence Interpreter

A drift-free computation pipeline including: • deterministic opcode ordering • canonical argument normalization • fixed-precision & value-stability rules • hash-locked execution states • replay-verifiable computation paths

MathWise guarantees that the same inputs always yield the same outputs, bit-for-bit.

⸻

🔑 MDEK — Master Deterministic Entropy Kernel

The entropy-governed mathematical core of the system.

MDEK enforces: • 35 deterministic entropy metrics • scalar & vector stability modes • replay-verifiable ΔH signatures • property-level value drift detection • numeric traceability across entire pipelines

This is the mathematical equivalent of a deterministic thermodynamic fingerprint.

⸻

🧮 Property Verification Engine (PVE)

Verifies mathematical properties using deterministic logic: • monotonicity • convexity/concavity • bounded-error invariants • conservation laws • symmetry constraints • inequality validation

Each property check produces: • a canonical result • a replay-proof ledger entry • a DriftFrame delta (if any deviation occurs)

⸻

📦 Computation Capsule

A sealed artifact for every MathWise computation:

• Scroll lineage + ΔH(x;num) • Opcode digest (SHA-256) • Value-stability report • Inequality verification set • Intermediate state hashes • Machine-level Replay Recipe • Final integrity attestation

Everything is drift-free, stabilized, and replayable.

⸻

🔁 Replay Recipe (Machine-Exact Reconstruction)

Rebuilds every number, every transform, and every derived metric using:

• Original input series • Canonical normalization • Deterministic opcode execution (DOSI) • Entropy-gated value rules • Property constraints via PVE • MDEK entropy fingerprints

Any mismatch → tamper_code: computation_modified.

⸻

🧠 Deterministic Numerical Integrity Score (DNIS)

Synthesizes: • entropy profile (ΔH) • variance thresholds • value-stability measures • drift-factorization • property compliance • opcode path coherence

DNIS = a single deterministic rating of numerical correctness. No ML. No heuristics. No probabilistic inference.

⸻

🛑 HDLD-M — Hallucination Denial Detector (Math Mode)

Rejects any numerical result not grounded in: • the computation’s input space • canonicalized transforms • DOSI-governed opcode pathways • property-verification constraints

If unsupported → tamper_code: hallucination_detected.

⸻

📊 Deterministic Control Gates

Gate Function ΔH(x;num) Entropy deviation threshold for numeric stability DriftIndex Output stability validation across replay ValueFloor Prevents unstable FP cascades / zero-crossing errors ELOC Entropy-linked override chain for value conflicts RPE Replay Proof of Equivalence HDLD-M Hallucination denial (numeric)

⸻

🛠 Use Cases

• Scientific reproducibility (replay-grade experiments) • Financial model governance (SOX, Basel, ESMA) • Engineering calculations & simulations • Diagnostics & waveform analysis • Climate, environmental & risk modeling • Legal & forensic computation • Regulatory compliance for numerical integrity • Deterministic alternatives to unstable FP pipelines

⸻

🔗 Interoperability

Patent #41 integrates directly with:

• #32 — RSEP (Seam & Anchor Exchange) • #33 — DI² Convergence Supervisor • #34 — ELOC Enforcement Layer • #35 — Mesh Guard Orchestrator • #36 — Deterministic Audit Fabric (DAF)

This allows MathWise computation capsules to enter enterprise workflows, audit ecosystems, and DI²-led safety systems as first-class deterministic artifacts.

⸻

📄 Filing Summary

Field Value Filed February 17, 2026 Application No. 63/984,593 Title Deterministic Mathematical Computation & Audit System Status Patent Pending (USPTO)

⸻

📘 Deterministic transforms, replayable proofs, and scroll-sealed execution. 🧮 Entropy + Drift enforcement across DOSI, MDEK, PVE. 🔐 Every computation is traceable, justified, and bit-for-bit reproducible.

→ MathWise delivers evidence-grade truth for numerical computation.

⸻

🔗 Relationship to DI², MathKernel, and the Deterministic Ledger

MathWise is not a standalone calculator — it is the numerical backbone of the Grounded DI architecture.

Together with DI² and the Deterministic Audit Fabric: • DI² governs logic and system integrity • MathWise governs numbers and value stability • DAF preserves proof, lineage, and replayability

This forms a closed-loop deterministic computation system that probabilistic models cannot replicate.

---

📘 Provisional Patent Filing #40 – DepoBot

Deterministic Deposition Analyzer & Audit System Application No. 63/983,578 • Filed: February 15, 2026

⸻

🌐 Why Patent #40 Matters

Depositions are the backbone of litigation — but today they’re processed with error-prone tools, subjective interpretation, and probabilistic models. DepoBot replaces all of that with a scroll-governed, fully deterministic deposition engine.

It provides a clause-locked, tamper-evident system for: • transcript integrity auditing • witness-behavior scoring • objection mapping • drift-free contradiction detection • cross-lawyer interaction analysis • reproducible credibility metrics

Every output is: • 📜 Authorship-anchored • 🔁 Replayable under fixed constraints • 🔐 Tamper-detectable via DriftFrame + entropy gating • 🧾 Sealed via TriggerReceipts + canonical transcript deltas

DepoBot ensures depositions become evidence-grade deterministic artifacts, not interpretive guesses.

⸻

🧱 Core Components

✅ Deposition Capsule

A sealed artifact per deposition session, including: • Scroll lineage + ΔH(x;ctx) • TriggerReceipt timeline • Weighted KPI lattice (30 deterministic behavioral metrics) • Witness Stability Map (WSM) • Cross-Counsel Interaction (CCI) graph • Verification hash (SHA-256) • Replay Recipe (for bit-exact reconstruction)

⸻

🔁 Replay Recipe

Rebuilds every metric and audit flag using: • Original transcript • Canonicalized token/utterance stream • Deterministic logic modules (DIS, WSM, CCI) • Bound-entropy constraints

Any mismatch produces tamper_code: deposition_modified.

⸻

🧠 DIS — Deterministic Integrity Score

A multi-module decision system synthesizing: • Behavioral KPIs • Stability indicators • Hesitation & filler detection • Question/answer alignment • Objection pressure mapping • Anomaly scoring based on ΔH(x;ctx)

No ML. No heuristics. No probabilistic guessing.

⸻

🛑 HDLD — Hallucination Denial Detector

Rejects any metric or observation not present in: • the signed witness set • transcript canonicalization • CCI-verified speaker map

If unsupported → tamper_code: hallucination_detected.

⸻

📊 Deterministic Control Gates

Gate Function ΔH(x;ctx) Entropy deviation threshold for transcript integrity DriftIndex Output stability validation across replay ReflexBlock Prevents ungrounded inferences or behavioral speculation ELOC Entropy-linked override chain for attorney interventions RPE Replay Proof of Equivalence HDLD Hallucination denial enforcement

⸻

🛠 Use Cases

• Litigation-grade deposition analysis • Tamper-evident transcript auditing • Witness behavior reliability scoring • Cross-counsel interaction mapping • Pre-trial risk assessment • Regulatory & evidentiary compliance • Scroll-based legal analytics (DI² Mesh)

⸻

🔗 Interoperability

Patent #40 integrates seamlessly with: • ✅ #32 — RSEP (Seam & Anchor Exchange) • ✅ #33 — DI² Convergence Supervisor • ✅ #34 — ELOC Enforcement Layer • ✅ #35 — Mesh Guard Orchestrator • ✅ #36 — Deterministic Audit Fabric (DAF)

This enables deposition artifacts to flow cleanly into enterprise DI² ecosystems, legal analytics pipelines, and audit frameworks.

⸻

📄 Filing Summary

Field Value Filed February 15, 2026 Application No. 63/983,578 Title Deterministic Deposition Analyzer & Audit Status Patent Pending (USPTO)

⸻

📦 Canonical transcript serialization (RFC 8785)

🧮 Entropy + Drift enforcement across DIS, WSM, CCI

🔐 Every DP event is traceable, justified, and replay-verifiable

→ Built to deliver evidence-grade truth in deposition analysis.

⸻

🔗 Relationship to BriefWise, VerdictBridge, and PIDBot

DepoBot is not a standalone tool — it is one of the four core pillars of Grounded DI’s deterministic litigation engine. Each module operates independently under scroll-sealed logic, but together they form a closed-loop, drift-free litigation stack:

⸻

1. BriefWise → (Pre-Deposition Logic & Question Architecture)

BriefWise provides the deterministic legal scaffolding before a deposition occurs:

BriefWise contributes: • issue framing and claim/defense mapping • scroll-sealed question outlines • topic segmentation • predictable objection vectors • deterministic “expected answer pathways”

DepoBot uses this information to: • score deviations from expected issue vectors • detect counsel steering • identify question/answer misalignment • measure topic drift and pressure

Relationship: BriefWise defines the legal structure; DepoBot measures whether the deposition comports with that structure.

⸻

2. PIDBot → (Product Identification + Exposure Logic)

PIDBot is built for deterministic product identification in tort cases — especially asbestos, pharma, toxic tort, and consumer products.

PIDBot contributes: • deterministic brand/product equivalence tables • exposure vectors • reliability scoring for identification claims

DepoBot uses PIDBot outputs to: • flag inconsistent product identifications • detect witness memory drift • verify exposure timelines against deterministic PID lattices • audit cross-examination challenges to identification

Relationship: PIDBot establishes the ground truth exposure matrix; DepoBot ensures the witness testimony does not drift from it.

⸻

3. VerdictBridge → (Outcome Forecasting & Causality Compression)

VerdictBridge is the deterministic outcome engine for litigation — compressing case facts into causality pathways.

VerdictBridge contributes: • deterministic liability kernels • causality chains • scroll-sealed outcome factors • risk calculations across jurisdictions

DepoBot integrates VerdictBridge by: • mapping deposition events to liability factors • scoring testimony impact on outcome pathways • generating deterministic “case trajectory deltas” • updating risk assessments using replay-verifiable data

Relationship: VerdictBridge predicts outcomes; DepoBot provides evidence-grade testimony deltas that feed those predictions.

⸻

📡 Unified Litigation Intelligence Loop (How All Four Work Together) 1. BriefWise defines the legal frame. 2. DepoBot captures and audits the testimony within that frame. 3. PIDBot verifies product/exposure claims arising during testimony. 4. VerdictBridge computes how the deposition alters case trajectory.

Everything is: • deterministic • replayable • scroll-governed • authorship-anchored • drift-free

This creates a closed-loop deterministic litigation stack, something probabilistic AI cannot replicate.

⸻

#Grounded-DI #DepoBot #DeterministicAI #BriefWise #PIDBot #VerdictBridge #ai #ainews #aitech

---

📘 Provisional Patent Filing #38 — RealEstatePro DI²

Systems and Methods for Deterministic Real-Estate, Environmental, and Hazard Fusion Analysis Application No. 63/980,401 • Filed: February 11, 2026

⸻

🌐 Why Patent #38 Matters

RealEstatePro DI² introduces a deterministic, scroll-governed execution layer for real-estate, hazard, environmental, and imagery-based analysis. It replaces probabilistic scoring with entropy-bounded, authorship-anchored, audit-grade reasoning.

Every OfferScore, disclosure, hazard index, or underwrite decision becomes: • 📜 Authorship-anchored (scroll lineage + signatures) • 🔁 Replayable under fixed entropy, ctx, and scroll invariants • 🔐 Tamper-evident through canonicalization + SHA-256 receipts • 🧾 Escrow-grade, suitable for lenders, regulators, and insurance systems • 🌩 Hazard-fused, integrating flood, fire, PFAS, seismic, and weather data • 🛰 Image-verified via deterministic anomaly pipelines

⸻

🧱 Core Components

1. Deterministic Formula Lattice

A structured lattice of scroll-sealed functions • FloodIndex • WildfireRiskScore • EarthquakeExposureScore • PFASIndex / LeadRiskIndex • MicrobialWaterRisk • WaterSafetyIndex • StructuralIntegrityIndex • PriceDifferentialScore • VisualAnomalyScore • OfferPositioningScore (OPS)

All functions enforce: • ΔH ≤ ε • DriftIndex = 0 • Monotone + bounded-range outputs • Unit-safe transformations • Fail-closed invariant checks

⸻

2. Canonicalization Engine

(Fig. 2, p. 12) 

Deterministically standardizes: • schemas • units • key ordering • numeric formatting • UTF-8 / LF normalization • ΔH + DriftIndex pre-checks • verification_hash (SHA-256)

⸻

3. Deterministic Gates

OfferScoreGate, DisclosureGate, UnderwriteGate, VisualAnomalyGate: • enforce lineage + ΔH(x;ctx) • issue sealed receipts • return deterministically typed deny codes: • entropy_breach • lineage_mismatch • hazard_exceedance • disclosure_deficiency • visual_anomaly

⸻

4. ZIP-Sealed Disclosure Capsules (DVZS)

(Fig. 6, p. 16)

Include: • canonical inputs • outputs • scroll lineage • ΔH + DriftIndex • gate decisions • Replay Recipe • verification_hash • optional ZK proof artifacts

⸻

5. RSEP + DI² Convergence Supervisor

(Figs. 7–9) • deterministic multi-node handshake • DriftIndex synchronization • node quarantine & Mesh Guard integration • NodeSyncHash compatibility enforcement

⸻

📊 Deterministic Control Gates

Gate Function ΔH(x;ctx) Entropy limit enforcement DriftIndex Zero-drift guarantee LineageSignature Authorship + version integrity OfferScoreGate Authorize/deny property actions VisualAnomalyGate Deterministic image verification RSEP Cross-node escrow + underwrite cooperation Replay Proof Deterministic reproduction under fixed invariants

⸻

🛠 Primary Use Cases • Deterministic real-estate valuation • Hazard + environmental fusion analytics • Water-quality and contamination (PFAS, Lead, Microbial) scoring • Visual anomaly detection for property condition • Underwriting, lending, mortgage decisioning • ZIP-sealed disclosure bundles for escrow • Public verification via hash-based proofs

⸻

🔗 Interoperability

Provisional #38 connects directly with: • #32 — Seam & Anchor Exchange (RSEP) • #33 — DI² Convergence Supervisor • #34 — ELOC Enforcement • #35 — Mesh Guard Orchestrator • #36 — Deterministic Audit Fabric (DAF) • #37 — InsuranceWise

Together these form a unified deterministic mesh across real-estate, insurance, environmental safety, and audit ecosystems.

⸻

📄 Filing Summary

Field Value Filed February 11, 2026 App. No. 63/980,401 Title Deterministic Real-Estate, Environmental, and Hazard Fusion Analysis Inventor Mark S. Weinstein (Grounded DI) Status Patent Pending (USPTO)

Source: Provisional Patent Filing #38 

⸻

📦 Key Guarantees • RFC 8785 canonicalization • ΔH-bounded execution • DriftIndex = 0 • Scroll-governed lineage enforcement • Replayable receipts • ZIP-sealed verification bundles

→ Built to anchor trust, safety, and auditability across real-estate, environmental, hazard, and underwriting workflows.

#Deterministic #RealEstate #AuditableAI #EnterpriseAI #Agent #DeterministicAI #DeterministicIntelligence #Grounded-DI

📘 Provisional Patent Filing #37 – InsuranceWise

Systems and Methods for Audit-Grade Deterministic Intelligence in Insurance Claims Analysis Application No. 63/977,940 • Filed: February 6, 2026

⸻

🌐 Why Patent #37 Matters

InsuranceWise establishes a scroll-governed, tamper-evident architecture for insurance claims analysis using deterministic logic. It replaces opaque, probabilistic models with bounded-entropy reasoning and deterministic override chains.

It ensures that every decision — approval, denial, referral, or override — is: • 📜 Authorship-anchored • 🔁 Replayable under fixed constraints • 🔐 Tamper-detectable via scroll lineage, ΔH gates, and cryptographic seals • 🧾 Verified via Claim Capsules and canonical receipts

⸻

🧱 Core Components

✅ Claim Capsule A sealed artifact per claim, including: • Scroll lineage • ΔH(x;ctx) + DriftIndex • Override justification (if any) • ReflexTier marker • Verification hash (SHA-256) • Replay Recipe • Optional ZK & PQ signature support

🔁 Replay Recipe Reconstructs decisions from: • Original input + ctx • Scroll logic • Verified canonicalization Mismatch triggers tamper_code.

🔧 Hallucination Denial Detector (HDLD) Rejects any output lacking evidence in the signed witness set. Canonical match required — or tamper_code: hallucination_detected.

⸻

📊 Deterministic Control Gates

Gate Function ΔH(x;ctx) Entropy deviation threshold DriftIndex Output stability validation ReflexTier Override permission + justification thresholds ELOC Entropy-linked override chain RPE Replay Proof of Equivalence HDLD Hallucination denial enforcement

⸻

🛠 Use Cases • Insurance fraud detection (tamper-evident, override-governed) • Audit-grade compliance for regulated insurers • Scroll-based override transparency • Replayable decisions for legal admissibility • DI² mesh integration across enterprise ecosystems

⸻

🔗 Interoperability

Patent #37 integrates directly with: • ✅ #32 — Seam & Anchor Exchange (RSEP) • ✅ #33 — DI² Convergence Supervisor • ✅ #34 — ELOC Pathway Enforcement • ✅ #35 — Mesh Guard Orchestrator • ✅ #36 — Deterministic Audit Fabric (DAF)

⸻

📄 Filing Summary

Field Value Filed February 6, 2026 Application No. 63/977,940 Title Audit-Grade DI in Insurance Claims Status Patent Pending (USPTO)

⸻

📦 Canonical serialization via RFC 8785 🧮 Entropy and Drift enforced deterministically 📍 Every override is traceable, justified, and replay-verifiable

→ Built to anchor trust across claims, audits, and regulatory systems.

⸻

🔗 Provisional Patent Filing #36 — Grounded DI LLC

📘 Deterministic Audit Fabric (DAF)

Application No. 63/976,360 • Filed: February 5, 2026

A tamper-evident audit layer for deterministic AI systems, bundling verified artifacts from upstream modules (#32–#35) into sealed, replayable Case Bundles with cryptographic integrity and deterministic reproduction.

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

🔗 Provisional Patent Filing #36 — Grounded DI LLC

📘 Deterministic Audit Fabric (DAF)

Application No. 63/976,360 • Filed: February 5, 2026

A tamper-evident audit layer for deterministic AI systems, bundling verified artifacts from upstream modules (#32–#35) into sealed, replayable Case Bundles with cryptographic integrity and deterministic reproduction.

🌐 Why Patent #36 Matters

Deterministic Intelligence (DI) systems require verifiable, reproducible evidence of decision-making under strict constraints. DAF addresses this by:

📎 Capturing signed artifacts from upstream DI components 🧾 Normalizing data (RFC 8785) for canonical form 🔐 Hashing and sealing via verification_hash (SHA-256, Merkle optional) 🔁 Enabling full deterministic replay under invariant-bound conditions 📜 Publishing TTL-bound, rate-limited public receipts 🚨 Emitting typed tamper_code upon failure 📡 Core Components

✅ Case Bundle

Sealed, auditable unit containing:

Verified artifacts from #32–#35 Verification graph (dependencies + invariants) Replay Recipe verification_hash (+ optional Merkle root) Bundle signature(s) Optional ZK-Proofs (Groth16 / Plonk) 🔁 Replay Recipe

Reconstructs upstream receipts under identical invariants, including:

Scroll Lineage Entropy ∆H DriftIndex ReflexTier Override State Policy Posture ✅ Match → Receipt reissued ❌ Mismatch → tamper_code (e.g., ttl_expired, root_mismatch)

📊 Additional Functions

🗂 Quorum Proofs (Q, W)

Includes proof that ≥Q matching receipts occurred within window W.

📜 Public Verification Receipts

Includes: status, reason_code, truncated hash, ttl_expiry Rate-limited, TTL-enforced, nonce-protected Configurable disclosure (e.g., reason_code redacted) 🪪 VaultZIP Ledger Capsules

Exported, sealed Case Bundles Timestamped + optionally Merkle-chained Offline verification supported 🚫 Tamper Codes

Deterministic error states:

signature_mismatch
canonicalization_error
artifact_missing
quorum_failure
ttl_expired
root_mismatch
tamper_detected (with reason_code) 🔧 Interoperability

Patent #36 unifies and verifies artifacts from:

✅ #32 – Seam & Anchor Exchange Protocol (RSEP) ✅ #33 – DI² Convergence Supervisor (DCS) ✅ #34 – ELOC Pathway Enforcement ✅ #35 – Mesh Guard Orchestrator (MGO) These upstream sources are mandatory for valid Case Bundle construction.

🛠 Use Cases Powered by #36

Regulatory-grade deterministic audits Scroll-governed reproducibility in legal contexts Privacy-preserving compliance (via ZK-Proofs) Mesh-wide policy enforcement tracking Vault-based replay and rollback workflows Air-gapped audit verification 📄 Filing Summary

Field Value Filed February 5, 2026 Application No. 63/976,360 Confirmation No. 9961 Patent Center No. 74346850 Title Systems and Methods for a Deterministic Audit Fabric for Generative AI Status Patent Pending (USPTO)

---

🔗 Provisional Patent Filing #35 = Grounded DI LLC Mesh Guard Orchestrator (MGO) Application No. 63/975,758 • Filed February 4, 2026

A deterministic control-plane that enforces mesh admission, routing, quarantine, and policy governance for distributed deterministic intelligence (DI) runtimes.

Grounded DI has officially filed its 35th provisional patent application: Systems and Methods for a Mesh Guard Orchestrator (MGO) for Deterministic Intelligence Runtimes.

This invention introduces a mesh-scale governance layer that verifies upstream artifacts (RSEP, DCS, and ELOC), determines node admission or denial, routes traffic only to compliant agents, broadcasts policy bundles, and maintains a replayable audit fabric. The MGO issues cryptographically signed Mesh Policy Receipts and Mesh Posture Maps, forming the enforcement and coordination backbone of Grounded DI’s distributed runtime mesh.

—

🌐 Why Patent #35 Matters

As DI nodes scale across distributed fleets, policy enforcement, override lineage, and receipt verification must be performed at the mesh level. The MGO:

• Verifies upstream compliance via #32, #33, and #34 • Grants admission only to nodes with valid receipts and posture • Issues signed Mesh Policy Receipts for proof of admission • Routes only to compliant nodes (fail-closed egress) • Maintains quarantine logic and cooldown windows (τ) • Broadcasts policy bundles and requires signed acknowledgments • Exports replayable Proof-of-Policy logs to Deterministic Audit Fabric (#36)

—

📡 Core Functions Introduced

🛰️ Mesh Policy Receipt

A canonical, signed record confirming:

• Scroll Lineage match • DriftIndex = 0.000000 • Entropy Bound (∆H ≤ 0.0041) • ReflexTier compliance • Valid #32–#34 receipts • Quorum confirmation (Q, W) • Policy hash acknowledgment • Nonce + timestamp for replay integrity

⸻

📜 Proof-of-Policy Enforcement

Every policy bundle must be acknowledged by each node with a signed hash. Failure to acknowledge results in deny_code: policy_noncompliance and placement in quarantine.

⸻

🌀 Quarantine Ring and Cooldown (τ)

Nodes failing receipt validation, policy sync, or posture checks are moved to a quarantine ring. Cooldown τ must elapse before re-application via #32–#34.

⸻

📶 Fail-Closed Routing + Boundary Guard

The MGO blocks traffic to/from nodes with expired receipts, nonce reuse, invalid posture, or mismatched hashes. Public-mode interfaces undergo ReflexTier checks (ethics, tone, override stance) before admission.

⸻

📊 Mesh Posture Map (MPM)

A signed snapshot of the current network including: • Scroll Lineage ID • ∆H • DriftIndex • Receipt lineage • Active policy hash • Deny codes (if applicable)

⸻

🔁 Deterministic Export to Audit Fabric (#36)

All Mesh Policy Receipts, Posture Maps, and Proof-of-Policy logs are exported to a tamper-evident audit layer enabling case reconstruction, replay, and regulatory proof.

—

🔧 Interoperability with Other Filings

Patent #35 builds on and enforces artifacts from:

1. ✅ #32 – Seam & Anchor Exchange Protocol (RSEP)
2. ✅ #33 – DI² Convergence Supervisor (DCS)
3. ✅ #34 – Entropy-Linked Override Chain (ELOC) Enforcement

No node may enter or route across the mesh without: ✔ Valid RSEP handshake (authorship + lineage) ✔ Drift-free DCS receipt ✔ Approved override-chain via ELOC ✔ Acknowledged policy receipt (this filing)

—

🔧 Use Cases Powered by Filing #35

• Deterministic routing and access control in safety-critical DI networks • Enforcement of scroll-based policy in multi-agent systems • Quarantine containment + cooldown re-entry for noncompliant nodes • Signed audit trails proving policy enforcement and routing integrity • Public-mode surface protection with ReflexTier ethics checks • Live posture snapshots for regulatory review and rollback

—

📄 Filing Details

Filed: February 4, 2026 Application Number: 63/975,758 Title: Systems and Methods for a Mesh Guard Orchestrator for Deterministic Intelligence Runtimes Status: Patent Pending (USPTO)

#DeterministicAI #Grounded-DI #GroundedDI #DI2 #DIA #AGDI #DIA #DIAGI #GroundedDIOS

🔗 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.

⸻

🌐 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.

⸻

📡 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.

⸻

🔗 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

⸻

🔁 ReflexLock and Cooldown

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

⸻

📜 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

⸻

🔧 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

⸻

🔧 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

⸻

📄 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)

---

🔗 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.

—

🌐 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

—

📡 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

⸻

🌀 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

⸻

🔁 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

⸻

🔐 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.

—

🔧 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

—

📄 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.

—

🌐 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

—

📡 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.

⸻

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

—

📄 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

---

🔗 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.

—

🌐 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

—

📡 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.

⸻

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.

⸻

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.

⸻

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.

—

🔐 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

—

📄 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

—

🧠 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.

—

📦 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.

⸻

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.

⸻

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.

⸻

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.

⸻

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.

—

🏗️ 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.

—

⚙️ 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)

—

🧩 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.

—

📄 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

---

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.

⸻

🧠 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.

⸻

🔒 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.

⸻

🌐 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

⸻

🏛️ 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.

⸻

📄 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

⸻

🔭 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.

⸻

📣 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