Plain-English translation: The canonical technical reference for Quantsultant’s verification kernel, the GRAMS™ manifold, our 10 modular API streams, and our 3 deployment runtimes (Python FastAPI, Go, and Native Rust).
Plain-English translation: Quantsultant is the deep-tech AI verification company and IP holder founded by Garrick Pinon (Founder, CEO & Chief ML & AI Architect) that builds deterministic infrastructure to drive AI hallucinations toward zero in high-stakes domains, starting with medicine and finance.
Modern foundation models (OpenAI, Anthropic Claude, Google Gemini, Meta Llama, DeepSeek) are probabilistic engines. In consumer chat, an occasional fabricated citation or drifted number is an annoyance; in clinical decision support, SEC 10-K financial restatements, or defense enclaves, a single hallucination is a fatal liability. Quantsultant solves this outside the stochastic model weights by wrapping any LLM or data pipeline in an external verification substrate.
Plain-English translation: Instead of asking a second AI model to grade the first AI model (which doubles latency and still hallucinates), our kernel checks every claim against a bounded mathematical surface before it reaches the user.
The hero verification API (exposed on quantsultant.dev and trustinference.app) inspects every claim your model generates against your source documents and domain constraints. Claims that clear the verification threshold are released in 2.5ms–35ms; ungrounded claims are truncated with a structured diagnostic reason.
GRAMS™ (Geometric Reasoning Anti-Hallucination Manifold System) is our proprietary, pre-patent geometric substrate. It treats multi-step reasoning as a trajectory across a bounded Riemannian surface, clamping semantic drift on Pass 1 and cutting wasted single-pass tokens, electricity, and cooling water by 44% (and multi-turn rework by 80.1%).
Standard vector RAG slices documents into arbitrary chunks and matches them by cosine similarity—failing when terminology drifts (e.g., Capex vs. Additions to PP&E) or polarity flips. GRMA replaces naive vector lookup with a compact proprietary index that runs on a single GPU (15.88 MB RAM footprint in Native Rust) and traverses verified geodesic neighborhoods.
Audited as a “multi-agent diagnostic reasoning engine inside a platform-level intelligence fabric” (Google Gemini 3.8 Flash High codebase audit, Aug 2026), the platform combines Geodesic Cost Analytics™ (per-token cost accounting down to fractions of a cent) with GeekVitals™ (our flagship clinical simulation vertical built shoulder-to-shoulder with a clinical expert).
Plain-English translation: One verification core is exposed through ten specialized REST and gRPC streams under unified Argon2id-scoped keys (tw_live_...).
| Canonical Docs Surface | Stream & Gateway Route | Primary Capability & Verified Outcome |
|---|---|---|
/docs/api/auth |
POST /v1/auth/argon2-verifyPOST /v1/demo/upload-dataset |
RFC 9106 Argon2id (m=65536, t=3, p=4) key exchange issuing scoped tw_live_... tokens and live client dataset upload auditing. |
/docs/api/trust |
Stream 01 · POST /v1/verify |
Flagship Trust Manifold enforcing the 18.5% → 0.08% clinical floor and −44% single-pass token reduction. |
/docs/api/semantic |
Stream 02 · POST /v1/reason/universal |
Universal Semantic & Domain Router over the compact single-GPU proprietary index across medicine, finance, accounting, and legal. |
/docs/api/metrics |
Stream 03 · POST /v1/geodesic/ingest |
Geodesic Cost Analytics™ per-token cost attribution, kWh/water telemetry, and O(1) cryptographic hash cache (−82% recurring load). |
/docs/api/observability |
Stream 04/05 · POST /v1/feynman/checkPOST /v1/pacing/cepeda |
Epistemic Observability: <2ms $0-token FeynmanCheck™ mastery verifier and Cepeda-Ebbinghaus™ retention pacing. |
/docs/api/harness |
Stream 06 · POST /v1/harness/wrap |
Model-Agnostic Anti-Hallucination Harness wrapping OpenAI, Claude, Gemini, Llama, or DeepSeek with zero fine-tuning. |
/docs/api/graph |
Stream 07 · POST /v1/tutorials/pipeline |
Geodesic Knowledge Graph & Deterministic 3D simulation pipeline with zero bounding-box overlap (IoU = 0). |
/docs/api/compute |
Stream 08 · POST /v1/chat/completions |
Zero-LangChain 2.5ms Compute Gateway eliminating middleware serialization bloat and doubling (~2×) GPU/TPU capacity. |
/docs/api/agents |
Stream 09 · POST /v1/ops/triage |
Multi-Agent Diagnostic Triage & Office Brain Ops across longitudinal SEC filings and 175 verified execution pods. |
/docs/api/etl |
Stream 10 · POST /v1/etl/jacobian |
Jacobian-Hessian ETL achieving 100% coverage across all 242/242 TPC-DI benchmark tables (ROC-AUC 0.87 → 0.925). |
Plain-English translation: All three runtime shells share the same verification core so teams can start with Python REST in minutes, scale to 100k+ streams in Go, or deploy air-gapped in Native Rust. All three shells are built, with hold-out enterprise validation runs scheduled.
Drop-in REST/JSON & zero-dependency Python 3.11+ engine (8ms Vultr cloud / 29ms edge / 304ms Crusoe GPU). Built for rapid enterprise charter integration without rewriting existing application code.
High-concurrency HTTP/2, gRPC, and Kafka gateway (5.4ms median latency) engineered for Tier-1 banks and multi-hospital health networks auditing 100,000+ concurrent streams inside customer VPCs.
Bare-metal, zero-GC, DoD Memory-Safe Language (MSL) compliant binary executing in 2.5ms local round-trip with a compact single-GPU proprietary index (15.88 MB RAM). Secure hardware-key delivery is on the roadmap and available on request.
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.