AI that controls the physical world — energy grids, vehicles, factories, infrastructure. Not chatbots. Not cloud dashboards. AI that controls physical infrastructure where latency and reliability are non-negotiable.
70% of AI pilots never reach production. For AI controlling physical infrastructure — factories, energy grids, vehicles — the failure rate is even worse. The problem is not the model. It's the system architecture. I close that gap with 17+ years of software engineering, product leadership, and management at companies where software meets the physical world: Cisco (network & video platforms, 100M+ users), Renault-Nissan-Mitsubishi (connected vehicle platform powering 4M+ users across 39 countries), and ABB E-mobility (EV charging infrastructure). Then I built Auralink: 1.7M lines of code co-developed with AI, ~20 autonomous agents, 78% incident resolution — arXiv preprint. I created the Physical AI Stack because no framework existed for organizations moving from cloud AI to systems that control real-world assets.
Strategy Theater: You pay $500K. You get a 300-slide deck. Nobody reads it. Nobody implements it. The consultants leave. You're exactly where you started, minus the budget. I've watched this destroy AI programs at Fortune 500 companies. Smart people. Big budgets. Zero production systems.
Consultant Dependency: The engagement never ends. You can't run your own AI because the consulting firm designed it that way. Every change request, every new model, every retrain cycle goes through them. You're not building capability. You're renting it. My goal is the opposite: I build myself out of a job. Every engagement includes capability transfer. You end stronger, not dependent.
Permanent Pilot: The demo works. Leadership is impressed. But it never graduates to production. No clear criteria. No architecture for scale. No plan for real users. Months pass. Budget burns. The pilot becomes a permanent state. At Hyperion, every initiative gets a 90-day checkpoint. It either ships, pivots, or gets killed. 'Permanent pilot' is not in my vocabulary.
Make physical infrastructure AI-native. 70% of AI pilots never reach production. For systems controlling energy grids, vehicles, and factories, failure is not an option. Every engagement is designed around the Physical AI Stack: from SENSE (data capture) through ORCHESTRATE (autonomous operation). I've done this at Cisco (network & video infrastructure, 100M+ users), Renault-Nissan-Mitsubishi (connected vehicles, major programs), ABB (EV charging infrastructure), and Auralink (400+ microservices, ~20 AI agents).
Diagnose the real problem--not the symptom the board noticed. Engineer for production, not demos. Pilot with clear graduation criteria and kill switches. Launch to real users with monitoring from day one. Optimize continuously against business metrics. Yield measurable impact and full capability transfer. This method is built on 17+ years of shipping at organizations where failure meant lost revenue, not lost slides.
Every initiative gets a 90-day checkpoint. Ship to production, pivot with purpose, or kill it. I will never let you burn budget on a pilot that has no path to production.
No partnerships. No kickbacks. No bias. When I recommend open source over proprietary, or build over buy, it's because the math says so for your situation. I have zero incentive to push any vendor.
I tell you what you need to hear. Sometimes that's 'don't do this.' Sometimes it's 'you're not ready.' Respectful pushback is part of what you're paying for. If you want a yes-person, I'm not it.
I build myself out of a job. Every engagement includes documentation, training, and knowledge transfer. When I leave, you run your AI yourself. That's success.
Hyperion is not for everyone. I'm the wrong choice if:
I'm for organizations whose AI must work in the physical world — where failure means stopped production lines, not a wrong chat response. If that's you, let's talk about your specific challenge.
30 minutes. No pitch. Just an honest conversation about your challenge and whether I can help. If I'm not the right fit, I'll tell you and point you somewhere better.