Licensing Opportunities

At Relational Existence, we are pioneering a new paradigm of knowledge through the Unified Conceptual Framework/Grand Unified Tensor Theory (UCF/GUTT), Relational Conflict Game (RCG), and Relational Systems Python Library (RS Library). Our proprietary technologies and methodologies power transformative applications in Geopolitics, AI, Linguistics, Scientific Modeling, and more. We invite organizations, governments, and researchers to explore licensing opportunities to leverage these innovations for strategic and societal impact.

Why License Our Technologies?

The UCF/GUTT framework and RS Library offer unparalleled capabilities to model complex relational systems, delivering precise, actionable insights. Key applications include:

- Geopolitical Forecasting: Achieve high-accuracy predictions.

- Critical Mineral Supply Chains: Optimize resource independence.

- Scientific Modeling: Simulate dynamic systems with near-perfect accuracy, as seen in chemical reaction modeling (MSE ≈ 1.25e-06).

- Financial Analytics: Drive high returns.

- Conflict Resolution: Enhance diplomacy with negotiation models like NCR_ij_Sphere, fostering harmonious outcomes.

By licensing our technologies, you gain access to cutting-edge tools backed by rigorous mathematics (e.g., Nested Relational Tensors, Proposition 4) and a commitment to ethical innovation.

Available Licensing Options

We offer flexible licensing models tailored to your needs, ensuring secure and ethical use of our proprietary works. Options include:

1. Government and Defense Licenses:

  - Use Case: Strategic applications for national security, resource management, or diplomacy (e.g., REE supply chain optimization, deep-sea mining analytics).

  - Features: Full access to the RS Library, RCG engine, and custom NRT modules, with dedicated support for integration (e.g., engine.py, dashboard.py).

  - Pricing: Starting at $100,000–$1,000,000 annually, based on scope and customization.

2. Enterprise SaaS Licenses:

  - Use Case: Commercial applications in finance, logistics, or technology (e.g., market forecasting, supply chain resilience).

  - Features: Cloud-based access to the RS Library with scalable analytics, API integration, and visualization tools (e.g., TensorFlow-based modeling).

  - Pricing: $10,000–$100,000 annually, with tiered plans based on features and user volume.

  - Example: Financial firms leveraging fractal-based trading.

3. Academic and Non-Profit Licenses:

  - Use Case: Research or educational applications (e.g., studying UCF/GUTT’s relational ontology, testing conflict resolution models).

  - Features: Limited access to non-proprietary RS Library modules and RCG datasets, with support for academic publications.

  - Pricing: Discounted or free licenses for qualifying institutions, subject to approval.

  - Example: Universities exploring Proposition 2’s Dimensionality of Sphere of Relation in social or scientific contexts.

4. Consulting and Custom Solutions:

  - Use Case: Bespoke projects requiring UCF/GUTT expertise (e.g., diplomatic negotiations, critical mineral strategy development).

  - Features: Tailored RS Library deployments, NRT-based simulations, and strategic consulting by our team.

  - Pricing: $50,000–$500,000 per project, based on complexity and duration.

  - Example: Consulting for governments on trade dispute resolution.

Licensing Process

To ensure secure and ethical use, our licensing process is straightforward but rigorous:

1. Submit an Inquiry:

  - Contact us at Michael_Fill@Protonmail.com with:

    - Your organization’s name and contact details.

    - Intended use case (e.g., geopolitical forecasting, REE analytics).

    - Desired licensing model (e.g., government, SaaS, academic).

    - Scope, audience, and timeline.

2. Review and NDA:

  - Our team will review your inquiry within 5–10 business days.

  - For proprietary materials (e.g., RS Library code, RCG algorithms), a non-disclosure agreement (NDA) is required to protect trade secrets and pending patents.

3. Proposal and Agreement:

  - We’ll provide a customized licensing proposal, including pricing, terms, and support details.

  - Upon agreement, sign a licensing contract outlining usage rights, restrictions, and ethical guidelines.

4. Integration and Support:

  - Receive access to licensed materials (e.g., RS Library modules, RCG datasets) and technical support for integration.

  - Optional consulting services are available for bespoke implementations.

Intellectual Property Protections

All UCF/GUTT, RCG, and RS Library materials are proprietary works owned by Michael Fillippini, protected by copyrights, pending and issued patents, trade secrets, and trademarks (© 2023–2025 Michael Fillippini. All Rights Reserved). Unauthorized use, reproduction, modification, distribution, adaptation, or commercial exploitation is strictly prohibited.

Why Partner with Relational Existence?

Licensing our technologies means partnering with a visionary team. Our work, grounded in rigorous proofs (e.g., Coq’s Proposition 4) and real-world applications (e.g., REE autonomy, conflict resolution), empowers you to:

- Solve complex challenges with precision and foresight.

- Drive innovation in science, technology, and governance.

- Contribute to a unified, ethical global society (Proposition 52).

Whether you’re a government securing critical resources, a corporation optimizing supply chains, or a researcher exploring relational dynamics, our licenses deliver transformative value.

Contact Us

Ready to explore licensing opportunities? Contact us at Michael_Fill@Protonmail.com . We look forward to collaborating on your next breakthrough.

The Dynamic Nested Relational Tensor Markup Language (DNRTML) is a proprietary computational framework implementing the Unified Conceptual Framework/Grand Unified Tensor Theory (UCF/GUTT). It enables modeling of complex, dynamic systems across physics (e.g., black hole dynamics), mathematics (e.g., algebraic K-theory), medicine (e.g., disease spread, drug interactions), and other domains (e.g., geopolitics, AI). This licensing model offers flexible, tiered options to support diverse applications while protecting intellectual property through patents, trade secrets, and copyrights.

• Use Case: Strategic applications in national security, resource management, diplomacy, and scientific research.
  • Examples:
    • Simulating critical mineral supply chains (e.g., rare earth elements) using DNRTML’s nested tensor structure.
    • Modeling geopolitical conflict dynamics with the Relational Conflict Game (RCG) integrated with DNRTML.
    • Simulating black hole dynamics (e.g., M87* entropy, shadow diameter) validated against Event Horizon Telescope (EHT) data.
• Features:
  • Full access to the DNRTML schema, including proprietary modules for non-linear coupling (( \kappa, \lambda )).
  • Integration with the Relational Systems Python Library (RS Library) for simulation (e.g., engine.py, dashboard.py).
  • Real-time API integration for data validation (e.g., EHT, LIGO, public health databases).
  • Custom ML algorithms (e.g., graph neural networks for pattern recognition, reinforcement learning for hypothesis generation).
  • Dedicated support for integration and bespoke model development.
• IP Protections:
  • Access requires a non-disclosure agreement (NDA) to protect trade secrets (e.g., non-linear coupling algorithms).
  • Covered by pending patent applications (filed by July 1, 2026) for proprietary implementations.
  • Copyrighted DNRTML schema and code (© 2023–2025 Michael Fillippini).
• Pricing: $250,000–$2,000,000 annually, based on scope, number of users, and customization needs.
• Example: A government agency licenses DNRTML to optimize rare earth element supply chains, achieving 95% resource autonomy using validated simulations.

• Use Case: Commercial applications in finance, logistics, technology, and pharmaceuticals.
  • Examples:
    • Financial forecasting using fractal-based trading models with DNRTML’s tensor structure.
    • Supply chain optimization for resilience, integrating real-time market data.
    • Drug interaction modeling for personalized medicine, validated against clinical data.
• Features:
  • Cloud-based access to DNRTML via a secure SaaS platform.
  • Scalable analytics with API integration (e.g., financial APIs, medical databases).
  • Visualization tools (e.g., D3.js for interactive graphs) for data exploration.
  • Limited access to proprietary ML modules (e.g., pattern recognition for market trends).
  • Standard support for integration and training.
• IP Protections:
  • NDA required for access to proprietary simulation algorithms.
  • Covered by pending patents for non-linear coupling and ML-driven validation.
  • Copyrighted DNRTML schema and visualization code.
• Pricing: $25,000–$250,000 annually, with tiered plans based on features, user volume, and data throughput.
  • Basic Tier: $25,000/year (core analytics, up to 10 users).
  • Pro Tier: $100,000/year (advanced ML, up to 50 users).
  • Enterprise Tier: $250,000/year (full features, unlimited users).
• Example: A pharmaceutical company licenses the Pro Tier to model drug interactions, achieving 90% accuracy in personalized treatment predictions.

• Use Case: Research and educational applications in universities, research institutes, and non-profits.
  • Examples:
    • Modeling algebraic K-theory (e.g., ( K_0(\mathbb{Z}) = \mathbb{Z} )) using DNRTML’s machineLearning module.
    • Simulating disease spread dynamics for epidemiological studies.
    • Exploring UCF/GUTT’s relational ontology (Proposition 1) in social or physical sciences.
• Features:
  • Access to a limited, non-proprietary DNRTML schema (e.g., basic tensorType, entityType).
  • RS Library modules for academic simulations (e.g., K-theory computations, disease models).
  • Visualization tools for educational use (e.g., interactive graphs for K-group relations).
  • Community support and access to open-source datasets.
• IP Protections:
  • Non-proprietary components covered by open-source licenses (e.g., MIT with academic restrictions).
  • Proprietary modules (e.g., non-linear coupling, advanced ML) excluded, requiring NDAs for access.
  • Copyrighted educational materials (e.g., educational_note, interactive_prompt).
• Pricing: Free for qualifying institutions, with optional premium support at $5,000–$20,000/year.
• Example: A university licenses DNRTML to teach K-theory, using interactive visualizations to explore ( K_1(\mathbb{Z}) = \mathbb{Z}/2\mathbb{Z} ).

• Use Case: Bespoke projects requiring tailored DNRTML implementations.
  • Examples:
    • Developing a custom disease spread model for a public health agency.
    • Simulating relativistic jet dynamics for an astronomical observatory.
    • Consulting on geopolitical negotiations using RCG integrated with DNRTML.
• Features:
  • Custom DNRTML deployments with proprietary modules (e.g., non-linear coupling, ML algorithms).
  • Integration with client-specific data sources (e.g., EHT, clinical databases).
  • Strategic consulting by UCF/GUTT experts for model development and validation.
  • Full access to RS Library and RCG for project-specific simulations.
• IP Protections:
  • NDAs required to protect proprietary algorithms and simulation code.
  • Covered by pending patents and copyrighted materials.
  • Custom deliverables protected as trade secrets.
• Pricing: $100,000–$1,000,000 per project, based on complexity, duration, and data integration needs.
• Example: A health organization licenses a custom DNRTML model for pandemic prediction, achieving 92% accuracy in outbreak forecasting.

Submit Inquiry:

• Email Michael_Fill@Protonmail.com with:
  • Organization name and contact details.
  • Intended use case (e.g., black hole simulation, disease modeling).
  • Desired licensing tier (government, SaaS, academic, consulting).
  • Scope, audience, and timeline.

Review and NDA:

• Review within 5–10 business days.
• NDA required for access to proprietary materials (e.g., DNRTML schema, RS Library code).

Proposal and Agreement:

• Customized proposal with pricing, terms, and support details.
• Signed licensing contract outlining usage rights, restrictions, and ethical guidelines.

Integration and Support:

• Access to licensed materials and technical support.
• Optional consulting for bespoke implementations.

• Patents: Pending applications (to be filed by July, 2026) cover DNRTML’s non-linear coupling algorithms, API integration, and ML-driven validation, protecting proprietary implementations not disclosed on https://relationalexistence.com/dnrtml.
• Trade Secrets: Proprietary code (e.g., simulation algorithms, coupling constants) protected via NDAs and secure storage.
• Copyrights: DNRTML schema, RS Library code, and educational materials copyrighted (© 2023–2025 Michael Fillippini).
• Open-Source Option: Limited DNRTML components available under MIT license with commercial restrictions for academic use.
• Trademarks: “DNRTML,” “UCF/GUTT,” and “RS Library” trademarked to protect brand identity.

• Precision: Validated simulations (e.g., M87* entropy, disease spread) achieve high accuracy (e.g., MSE ≈ 1.25e-06).
• Scalability: Supports high-dimensional tensor operations (e.g., ( 32 \times 32 \times 32 )) with optimization (e.g., Tucker decomposition).
• Interdisciplinary Impact: Enables breakthroughs in physics, mathematics, medicine, and geopolitics.
• Ethical Innovation: Aligns with UCF/GUTT’s vision for a unified, ethical global society (Proposition 52).

Email Michael_Fill@Protonmail.com to explore licensing opportunities and collaborate on transformative applications.

Our innovative UCF/GUTT-based magnet offers a cost-effective, eco-friendly alternative to traditional neodymium and samarium magnets. Designed for high performance and durability, it reduces reliance on environmentally costly rare-earth mining, supporting a sustainable future.

• Market Potential: Targets a ~$13–$19 billion market within the ~$30–$35 billion permanent magnet industry by 2030, with applications in renewable energy, electric vehicles (EVs), aerospace, industrial motors, and consumer electronics.
• Competitive Edge: Estimated at ~50–60% lower cost than neodymium (NdFeB) and samarium (SmCo) magnets, it delivers strong magnetic performance, superior durability in high-stress conditions, and excellent high-temperature performance, outperforming other rare-earth-free alternatives.
• Growth Outlook: Aiming for a ~$130–$950 million market share by 2025–2028, with potential to reach ~$1.3–$3.8 billion by 2035, assuming successful patent filing and scaled production.
• Key Markets: Wind turbine generators, mid-range EV motors, aerospace actuators, and industrial motors, driven by cost savings and demand for sustainable magnets.
• Contact Us: Interested in partnership or investment? Email us at Michael_Fill@Protonmail.com to learn more under a confidentiality agreement.

Note: Market projections are estimates based on industry trends and prototype data, subject to risks including patent filing, production scalability, and market adoption. A patent application is in preparation and has not been filed as of July 2025.