Subject: Revolutionizing AI: Opportunity in Next-Gen Machine Learning Technology

As a professor of computer science and software engineering for many years, including at a Texas A&M campus, I had been pondering the pressing need to improve AI computational paradigms. In mid-2024 I had the patent idea that can supplement or replace the foundational “backpropagation” system ubiquitously used in AI. Expert legal work got this patent issued in March 2025. MLiglon continues to buttress and expand the IP as part of a long-term strategy built around the scalable technology. This technology has the possibility to be licensed and used globally, eventually and lucratively in hardware chips. As of September 22nd, we also have this working with NLP, scoring 94.37% accuracy on the AG New Corpus text classification benchmark with 120k parameters, other implementations are using millions (usually 10-100M).

Why this Matters:

Problem: Backpropagation, the cornerstone of AI training, is inefficient, costly, and energy-intensive—limiting scalability for enterprises and startups alike. The models produced are not particularly efficient in inference as well.
Solution: Our patented MLiglon technology (issued March 2025, US-12,242,946-B1, attached) reimagines neural network optimization, offering faster training and inference times, better accuracy, and thereby lower computational costs (see attached 5 benchmarks).
Market Potential: This innovation is primed for global licensing across industries—from enterprise AI to autonomous systems—targeting a $100B+ market.

Investing in MLiglon AI:

Proven Credibility: Developed by a current computer science and software engineering professor with 20+ years of research experience and a track record of industry collaboration.
Defensible IP: A granted U.S. patent (with international filings underway) creates a moat against competitors.
Scalable Business Model: Revenue streams include SaaS licensing, enterprise integration, and AI hardware partnerships.
Traction: Validated by leading patent attorneys, technical advisors, and early conversations with chipmaker teams.

I’d welcome the chance to discuss how this opportunity aligns with your portfolio’s focus on high-impact, deep-tech innovation. Let’s connect to explore next steps. For quickest response I invite you to contact our Financial Officer:

Dr. Michael Scott Brown at 📞 202-257-1067 or 📧 michael_s_brown@mliglon.com.

Best Regards,

Dr. Michael Pelosi
Co-Founder, MLiglon AI Corporation 🇺🇸 US (Texas) S-Corporation
📞 430-274-6154 | 🌐 Website: https://www.mliglon.com
📧 michael@mliglon.com – Assistant: Rachel Halbakken 📧 rachel@mliglon.com

MLiglon Corporation

MLiglon AI (creator of Integer Gate Logic, “IGL”) is a Texas based corporation offering the next generation of products and platforms for training neural networks. Using patented, proprietary technology, IGL networks train faster, predict more accurately, reduce energy consumption, provide enhanced parallelization and scalability, and promote model transparency. IGL addresses all of the most pressing AI industry needs, including faster and better performance models at lower cost. IGL is the first truly revolutionary AI neural network architecture in 50 years, and could make backpropagation and other gradient-descent training solutions a thing of the past.