What began as a passion project evolved into something more. We’re proud of what we’ve created and even more excited for what’s ahead.
The Origins of TAIE & V2G…
TAIE began as a practical experiment.
The original objective was narrow: to help a small mining company identify elusive gold mineralization on ground where conventional approaches had failed. There was no intention to develop a unified Earth model, no aspiration to influence economic geology, and no broader ambition beyond solving a specific, real-world problem.
Over the course of a year of intensive development, TAIE evolved through multiple iterations into something deeper, broader, and more predictive than initially anticipated. What emerged was not a single insight, but a layered framework. The Unified Earth System Model (UESM) is the cumulative result of that process.
UESM is a mathematics-based, structure-first model. Its validity is tested in only one way: when TAIE applies UESM to known and documented mineral systems, the results align with real-world observed outcomes — both successes and failures. This includes systems that prospered and systems that collapsed. TAIE does not explain only wins. It explains losses with equal clarity. (See the TAIE Walk-Away case.) This is KEY - we believe that future investors and miners will come to rely on TAIE and UESM to determine mine project viability.
TAIE was developed by an AI architect with more than 25 years of experience in information systems and cybersecurity, not by a traditional geologist or mining engineer. This turned out to be a blessing.
TAIE was built from a blank sheet, without reliance on academic convention, disciplinary silos, or inherited assumptions. The only governing constraint was verifiable, measurable structural truth. If an observed pattern could not be supported by structure, it was discarded — regardless of precedent.
The development methodology was consistent throughout:
Follow structure relentlessly.
Extract repeatable patterns.
Accumulate and recombine those patterns to reveal deeper structure.
Use any discipline that adds explanatory power.
As a result, TAIE incorporates validated concepts from physics, geology, thermodynamics, fluid dynamics, chemistry, economics, systems engineering, program management, and applied philosophy. The source of an idea is irrelevant; its ability to constrain reality is what matters.
It is important to be explicit: the architect behind TAIE does not claim mastery of every contributing domain, nor the ability to derive every equation embedded in the system. That is not the point. TAIE reflects a different premise — that artificial intelligence elevates the disciplined generalist. Progress comes not from narrow specialization, but from the ability to integrate all valid data and methods in pursuit of structural truth. Solo development has turned out to be a blessing - design by committee of experts would have slowed discovery and development.
TAIE is the product of persistence, methodological rigor, and refusal to accept explanations that fail under depth, time, or economic stress.
That orientation — not novelty — is what makes TAIE effective.