Zero-Training AI™ Demos
Budget Allocator
Automatically allocate a starting budget across hundreds of meda buys for Half Hours of television time for infomerrcials to maximize overall NET PROFIT.
Try Budget Allocator
Drone Hover Stabilizer Simulation
A small quad-drone icon tries to remain level. You press buttons like Wind Gust, Tilt, and Disturbance, and the drone re-stabilizes instantly. Visual scaling represents relative control energy, not physical motion.
Try Drone Hover
Robot Arm Balancer
A simple animated 2-joint “robot arm” tries to hold a target point. When user moves the target, the arm smoothly finds a stable configuration. No “machine learning”—just pure real-time control.
Try Robot Arm Balancer
LLM Token Governor (Hallucination Eliminator)
User types a prompt. Model outputs 5 candidate sentences. Zero-Training AI™ filters them and highlights the “safe, consistent, non-hallucinated” one.
Try LLM Token Governor
Zero-Training AI™ demonstrates how deterministic decision systems can operate without training data, datasets, or machine learning models. The systems shown here evaluate candidate actions in real time within a defined Decision Space, producing stable and explainable outcomes across multiple domains.
Legal & Technical Disclaimer
Zero-Training AI™ is a proprietary decision-optimization technology demonstrated here for informational and educational purposes only. The demonstrations on this website are simplified visual and interactive examples intended to illustrate conceptual behavior, not operational systems.
These demos do not represent physical simulations, real-world control systems, autonomous vehicles, medical devices, financial instruments, or deployed safety-critical systems. Any visual motion, scaling, or behavior shown is a mathematical or illustrative abstraction and should not be interpreted as modeling real energy, force, thrust, risk, or physical dynamics.
Zero-Training AI™ does not rely on training data, datasets, machine learning models, or statistical inference. Outputs shown are generated through deterministic mathematical evaluation and decision-selection logic applied at runtime.
No representation is made that these demonstrations are complete, production-ready, error-free, or suitable for any specific use without further engineering, validation, testing, and regulatory review.
This website and its contents do not constitute an offer to sell, a solicitation to buy, or a solicitation of investment interest in any security, product, or business opportunity. The site is not intended to solicit investors.
No Professional Advice Disclaimer
Nothing on this website constitutes legal, medical, financial, engineering, or professional advice of any kind.
Intellectual Property Notice
Zero-Training AI™, associated terminology, and underlying methodologies are proprietary and may be protected by patents, patent applications, trademarks, and other intellectual property rights. Unauthorized use or reproduction is prohibited.
Limitation of Liability
In no event shall the owners, developers, or affiliates of Zero-Training AI™ be liable for any direct, indirect, incidental, consequential, or special damages arising from the use of or inability to use these demonstrations.
No Regulatory Approval Disclaimer
These demonstrations have not been reviewed, approved, or certified by any regulatory authority and are not intended for regulated or safety-critical use.
No Warranties Disclaimer
All content is provided “as is” without warranties of any kind, express or implied, including but not limited to accuracy, completeness, fitness for a particular purpose, or non-infringement.