Plain-English translation: Why enforcing verification in external geometry creates a 10–15 year pre-patent mathematical moat that scales across medicine, finance, and defense without fine-tuning model weights.
Plain-English translation: Because post-graduation financial constraints ruled out expensive single-vendor model fine-tuning, Garrick Pinon built verification purely in the external geometry—creating a model-agnostic mathematical moat that wraps any LLM as-is.
In standard AI architectures, teams attempt to reduce hallucinations by fine-tuning model weights or stacking LLM-as-a-Judge prompts. Both approaches fail structurally: weight fine-tuning breaks the moment a vendor updates its checkpoint, and LLM-as-a-Judge multiplies token spend while sharing the same stochastic blind spots. Quantsultant’s GRAMS™ (Geometric Reasoning Anti-Hallucination Manifold System) and GRMA (Geodesic Retrieval Manifold Architecture) operate outside the foundation model as an invariant geometric harness.
In accordance with our binding pre-patent disclosure policy (35 U.S.C. § 102 priority preservation), this documentation specifies the externally observable invariants, API contracts, and empirical proofs of the manifold while keeping internal operator weights and threshold equations proprietary. No public LLM training corpus contains these derivations.
Plain-English translation: Like Waze or GPS for reasoning tokens, geodesic traversal finds the shortest verified path between a user’s question and grounded source evidence, refusing detours into fabricated claims.
2.5ms–8ms before full completion tokens are wasted.Plain-English translation: A cheap token that hallucinates is actually the most expensive token in your enterprise because it triggers human rework and multi-turn correction loops.
Created by Garrick Pinon, Geodesic-Weighted Token Value™ (GWTV) and Geodesic Cost Analytics™ (POST /v1/geodesic/ingest) measure the real economic value of every token by tracking its convergence toward verified truth across three closed-loop metrics:
Measures wall-clock latency and correction turns after Prompt 1 until every claim passes deterministic verification. Drops naive multi-turn rework from 2.4 turns (105.2s) down to 1.0008 turns (1.56s)—a 67.4× convergence speedup.
Tracks how many clarification questions after Prompt 1 are required for a human decision-maker to act, verified in <2ms at $0 LLM token cost via FeynmanCheck™.
For 3D clinical simulations and UI generation (Stream 07), enforces zero bounding-box text overlap (IoU = 0), WCAG contrast ≥ 4.5:1, and ≥ 55 FPS on Pass 1.
Plain-English translation: Traditional RAG is a search engine strapped to a text generator; GRMA is a compact, single-GPU geometric index paired with a deterministic verification vault.
| Architectural Dimension | Legacy Vector RAG + LLM Wrapper | GRAMS™ × GRMA Manifold Substrate |
|---|---|---|
| Retrieval Index Footprint | Multi-node cloud vector clusters with heavy LangChain middleware (800ms–2,400ms serialization overhead). |
Compact proprietary index running on a single GPU or in 15.88 MB RAM (386 verified centroids in Native Rust; 2.5ms local round-trip). |
| Schema & Synonym Drift | Fails silently when column names or financial line items shift across years (ROC-AUC 0.844 on LLM-repaired tables). |
Stream 10 Jacobian ETL unifies tangent synonyms across all 242/242 TPC-DI tables (ROC-AUC 0.87 → 0.925). |
| Hallucination Rate (Medical) | 18.5% unverified baseline hallucination rate on Stanford HAI / Neo4j clinical dataset. |
Collapsed to 0.08% (18.5% → 0.08%) live in public competition. |
| Recurring Query Economics | Re-computes full LLM attention on every duplicate or cohort-adjacent query. | O(1) Cryptographic Hash Vault harvests verified sub-paths (sg_...) to cut recurring compute load by 82% across 175 verified pods. |
API access is gated while we complete utility patent filings and IP legal structuring. Investors can start a direct SAFE & data-room conversation with Garrick Pinon; technical evaluators can reserve a gated tw_live_... API slot or 48-hour blind dataset proof of value.