Advanced AI Intelligence Monitoring

Our quantum-inspired mathematical frameworks (HIGL, QGT, IGBP) provide enterprise-grade AI transparency through geometric intelligence pattern detection running on standard GPU hardware.

"Quantum-inspired mathematical rigor with immediate deployment value on existing enterprise infrastructure."

Research-Driven Enterprise AI Solutions

Mathematical Foundations for Advanced Intelligence Monitoring

Our approach to AI intelligence monitoring combines rigorous mathematical research with practical enterprise solutions. Through systematic development of three core frameworks, we've created a comprehensive platform for advanced AI transparency and intelligence pattern detection.

Core Mathematical Frameworks

HIGL (Hilbertian Information Geometry of Learning)

Unifies Hilbert space semantics with information geometry for rigorous neural network analysis.

  • • Typed Hilbert construction for semantic neural computation
  • • Quantum-inspired differential geometry applications
  • • Tractable computational probes (Hutch++, SLQ)

QGT (Quantum-Inspired Geometric Tensor) Processing

Q = g + iΩ decomposition providing capacity and dynamics insights.

  • • Real part (g): Fubini-Study metric for AI expressivity
  • • Imaginary part (Ω): Berry curvature for path-dependent behavior
  • • GPU-optimized for real-time enterprise analysis

IGBP (Information Geometry Balance Principle)

Mathematical condition ‖∇S‖² ≥ ‖Ω‖ ensuring stable learning dynamics.

  • • 6 entropy measures for comprehensive monitoring
  • • Validated across 5 architecture families (A4-GNN, Fourier, GNN, HAM, VAE)
  • • Enterprise-ready stability predictions
"Mathematical transparency through geometric principles - not post-hoc explanations, but architecturally embedded clarity."

These frameworks enable our Advanced AI Intelligence Monitoring platform—providing enterprises with research-proven methods for AI transparency, safety validation, and regulatory compliance through mathematical rigor rather than statistical approximations.

The Founder's Journey

An Unconventional Background

Dimitry Jean-Noel II

Founder combining unconventional background with mathematical pattern recognition to solve enterprise AI transparency challenges through working technology.

Key Experiences

  • Military Precision: US Marine Corps Reserves (2017-2023)
  • Detail Execution: Carpentry & construction (2020-2023)
  • Risk Analysis: Financial services (2023-2024)
  • Technical Foundation: AI coding bootcamp (2024-2025)
  • Customer Solutions: Lowe's Pro desk (2024-2025)
  • Mathematical Discovery: Quantum mechanics & group theory

The Enterprise Challenge

"How do you make AI decisions auditable for boards, regulators, and customers without sacrificing performance or requiring post-hoc explanations?"

The Insight: Build transparency into the decision-making process itself through mathematical frameworks that make reasoning visible by design, not by addition.

Current Achievement

Working AI model testing platform with enterprise authentication, compliance reporting, and mathematical transparency frameworks—proving the concept works in production.

Our Mission & Vision

Mission

Enable enterprise AI transparency through rigorous mathematical frameworks. Our HIGL, QGT, and IGBP systems provide verifiable intelligence monitoring for regulated industries requiring mathematical proof rather than statistical approximations.

Vision

Become the standard for AI intelligence monitoring in enterprise environments. Mathematical transparency as the foundation for trustworthy AI deployment across industries requiring regulatory compliance and stakeholder accountability.

Core Values

Truth through mathematics
Transparency by design
Innovation with responsibility
Collaboration over competition

Technical Innovation & Research

Concrete achievements in AI intelligence monitoring and mathematical transparency

HIGL Framework Implementation

Complete mathematical framework bridging Hilbert space semantics with neural computation.

  • • Hutch++ algorithm for trace estimation
  • • Stochastic Lanczos Quadrature (SLQ)
  • • Matrix-Rényi entropy computation

QGT Analysis Engine

Production-ready quantum geometric tensor decomposition with GPU optimization.

  • • Real-time Fisher-Rao metric calculation
  • • Berry curvature dynamics analysis
  • • Enterprise-scale performance optimization

IGBP Validation System

Comprehensive entropy monitoring with stability prediction across architecture families.

  • • 6 entropy measure suite
  • • 5 architecture family validation
  • • Predictive stability analytics

Enterprise Platform

Full-stack intelligence monitoring platform with advanced authentication and compliance.

  • • Multi-tier subscription architecture
  • • API-first intelligence analysis
  • • Regulatory compliance reporting

Current Technical Achievements

Production Platform

  • • Working AI model safety database with API endpoints
  • • 60+ safety prompts testing framework
  • • Real-time trust scoring and safety grade generation
  • • Enterprise subscription and authentication system

Research Implementation

  • • QGT-based coherence analysis system deployed
  • • Interactive model comparison and filtering
  • • Compliance reporting for enterprise clients
  • • Multi-tier platform architecture operational

Company Roadmap & Vision

Scaling from solo founder to enterprise AI intelligence monitoring leader

Journey So Far

Mar 2025

Research Breakthrough

Mathematical framework discovery while balancing development work

May 2025

Full-Time Commitment

Transitioned to full-time development and company formation

Jun 2025

Platform Deployment

Working AI model database with enterprise features launched

Next 12 Months

Q3 2025

Customer Validation

Startup and Growth tier customer acquisition with case studies

Q4 2025

Research Publication

ArXiv publication of foundational papers and academic partnerships

Q1 2026

Enterprise Launch

Full enterprise tier launch with Fortune 500 pilot programs

Year 1: Foundation

  • • Scale Startup/Growth tiers to 100+ customers
  • • Complete NVIDIA Inception program
  • • Publish research papers and build academic credibility
  • • Develop enterprise pilot program
  • • Establish regulatory compliance expertise

Year 2-3: Scale

  • • Launch enterprise tier with Fortune 500 clients
  • • Build strategic partnerships with consulting firms
  • • Expand team: AI researchers, enterprise sales, compliance
  • • International expansion (EU market focus)
  • • Series A fundraising for accelerated growth

Year 4-5: Leadership

  • • Market leader in AI decision transparency
  • • Platform for 10,000+ enterprise models
  • • Industry standard for AI audit requirements
  • • Global regulatory compliance expertise
  • • Strategic acquisition opportunities or IPO

Current Status: Proving the Concept

We've moved from theoretical research to working platform. The mathematics work, the technology is deployed, and enterprise features are operational.

Ready for the next phase of growth.

Join Our Mission

We're building the foundation for trustworthy AI, one mathematical proof at a time. Whether you're an enterprise seeking verifiable AI, an investor looking for the next breakthrough, or a talented engineer ready to shape the future—we want to hear from you.

For Enterprises

Deploy AI with mathematical guarantees in regulated industries.

For Investors

Join us in defining the trustworthy AI category.

For Talent

Work on fundamental problems at the intersection of math and AI.

"The best ideas often come from those who don't know what's 'impossible.'"