Company

AuraSpark Technologies LLC develops AI governance and auditable autonomy architecture for environments where decisions must be traceable, explainable, and defensible.

Founder

Richard J. Mitchell, ESEP, MBA

Founder and CEO of AuraSpark Technologies LLC. Holds an Expert Systems Engineering Professional (ESEP) certification through INCOSE—one of the highest designations in systems engineering—and an MBA from the University of Florida.

More than 30 years of experience in complex systems engineering and safety-critical platform development, including a former Senior Architect role at CAE, one of the world’s leading simulation and training companies. His background in defense simulation and regulated systems directly informs AuraSpark’s architecture-first approach to AI governance.

Recent milestones

  • arXiv submission (March 2026, under review): Beyond Symbolic Control—formalizing genuine vs. nominal human oversight as a systems engineering design requirement
  • I/ITSEC 2026: Abstract under review on AI governance for autonomous systems in simulation and defense training
  • MODSIM World 2026: Abstract under review
  • USPTO patent portfolio: Active prosecution across the AURA family spanning defense, clinical, and enterprise governance architectures
  • INCOSE membership: Active ESEP-certified member of the International Council on Systems Engineering

What we believe

Genuine oversight, not symbolic

The humans nominally in charge of AI decisions must have the architecture to actually exercise that authority—not just sign off on outputs they cannot audit.

Governance before deployment

Requirements for human oversight must be specified before architecture is defined. Retrofitting governance after deployment is expensive and structurally compromised.

Built for regulated reality

Real-world regulated environments require evidence, safety cases, and operational constraints—not black-box assurances or lab benchmarks.

Focused initial deployments

DoD AI governance

The AURA patent portfolio provides constraint enforcement and genuine human oversight architecture for U.S. Department of Defense AI-enabled autonomous systems—making decisions auditable, overridable, and accountable.

Architecture overview

Rugged adaptive drone

A patent-pending multirotor with redundant systems, fail-operational autonomy, and the ability to adapt behavior on the fly as sensors degrade, conditions shift, or components fail. Built for environments where reliability is non-negotiable.

Drone Works →

Collaboration

Co-founders

We’re forming a small founding team with deep capability in autonomy, AI governance, and regulated systems.

Explore roles

Investors

We support investor diligence under NDA, including architecture summaries, IP strategy, and milestone-based plans.

Investor overview

Pilots & partners

Licensing discussions, design partnerships, and operator collaborations welcome under NDA.

Contact