Pre-physical optimization
We allow instability to emerge in non-physical modeling environments, then recover to viable states before any real-world transition.
Independent R&D Lab · Michigan, USA
Applied physics and AI systems built for real-world stability
We develop patent-pending frameworks that stress-test instability before deployment, validate through digital twins, and translate advanced mathematics into practical engineering outcomes.
5
Filed patent applications
11
Public project pages
A clearer public narrative
This homepage is intentionally written for people first: researchers, evaluators, and serious partners. Public pages explain what each system does, while implementation-sensitive details remain in controlled channels.
Cross-domain stability verification
We evaluate adversarial and physical disturbances under a unified stability lens, helping bridge AI security with control-system reliability.
Research-to-implementation pathway
Our process moves from theory and simulation to constrained deployment with measurable checks, documentation, and governance.
Five filed patent applications — foundational frameworks
We communicate these tracks at an architecture level in public. Detailed implementations, benchmarks, and reduction-to-practice materials are released selectively and responsibly.
U.S. Provisional Applications 63/999,270 (March 7, 2026), 64/029,363 & 64/029,394 (April 4, 2026), 64/030,975 (April 6, 2026). U.S. Non-Provisional Application 19/560,051 (March 8, 2026). All verifiable at USPTO Patent Center.
Track 01
Pre-Physical Expansion & Gaussian Well Stabilization
A framework for exploring divergent states in non-physical realms, guiding recovery toward viable optima, and gating transition to physical realization only after passing validation.
Track 02
Polyvalent Stability Theory (PST)
A unified approach to adversarial and control-system stability analysis using shared criteria, cross-domain reasoning, and hybrid verification methods.
Track 03
WoofWizeX-FRS Behavioral Intelligence
Wireless behavioral monitoring for companion animals using ambient field sensing, authenticated activation, and privacy-preserving computation architecture.
Track 04
Unified AI Compliance Architecture
Multi-domain AI compliance through penalty-augmented objectives, cognitive integrity monitoring, and imaginary realm auto-repair gating mechanisms.
Track 05
Polyvalent Excitation Framework (PEF)
Manifold-valued configuration analysis, spark-like radiant propagation, invariant kernel preservation across domain projections, and survivability-gated embodiment in multi-domain computational systems.
Research project index
One place to access every active public page.
Pre-Physical Expansion Framework
Optimization before physical realization in controlled expansion realms.
Polyvalent Stability Theory (PST)
Unified cross-domain adversarial and system stability verification.
PAID-FR 4.0
Plasma-focused digital twin and stability optimization workstream.
Omnimathematics
Core mathematical infrastructure and optimization mechanics.
OURS — AI Compliance Architecture
Mathematical compliance enforcement that makes non-compliant AI behavior structurally expensive.
WoofWizeX-FRS
Non-invasive animal behavioral intelligence through ambient field sensing.
Polyvalent Excitation Framework (PEF)
Manifold-valued configuration analysis and survivability-gated embodiment.
BoloBeam Mk. II
Precision low-frequency acoustic systems and control methods.
OmniX
AI security and cognitive integrity architecture research.
DNEA
Advanced systems analysis in constrained operational domains.
theFreq
Frequency-domain tooling and practical control primitives.
Technology Platform
Integration layer connecting research, simulation, and deployment.
aiGENT Cognitive Security
Agentic AI workflows with stability and security boundaries.
Who we work with
- • Research groups evaluating novel optimization and stability models.
- • Academic collaborators interested in reproducible multiphysics workflows.
- • Strategic partners seeking rigorous technical diligence before integration.
Disclosure and access model
Public content is architecture-level by design. Implementation-sensitive details, benchmarks, and package-level documentation are shared under NDA for qualified collaboration and review.
Start NDA access workflowConnect
Research collaboration, technical evaluation, investment, or licensing inquiries. All messages go directly to Marc Tuinier.
Direct contact
- Founder: Marc@mttechindustries.com
- General: info@mttechindustries.com