Joe Quenneville
CO-FOUNDER & CEO
35+ years in cybersecurity and enterprise technology. CISO-level experience across financial services and defense - the person asking the hard questions in the room.
Our Mission
We built this because
the question needed asking.
Enterprises are spending billions on AI they don't own, can't control, and may not be able to afford in three years. AI Standards Inc. exists to change that.
AI should be an asset - not a risk.
The enterprise AI market was built around a model that benefits vendors: usage-based pricing, proprietary APIs, and infrastructure you'll never own. Every token you process makes your vendor bigger and your exit harder.
We deploy production-grade AI on hardware you own, in your facility, under your control. Not as a philosophical statement - as a practical business decision with a measurable ROI and a break-even you can put on a spreadsheet.
We don't replace your team. We augment it with engineers who stay until the system is running, the models are fine-tuned on your data, and your people know how to use it. We meet our customers at their need level.
You own the hardware
No usage fees. No API costs. No vendor dependency. Your AI runs on your servers, in your building, on your terms.
Your data never leaves
Every query, document and output stays inside your network perimeter. GDPR, HIPAA, SOC 2 - your compliance team stops worrying.
Fine-tuned for your business
Generic models give generic answers. We fine-tune on your domain data so the AI actually understands what your company does.
Cost you can model
Hardware amortizes. Power is predictable. Your AI costs don't double when your usage doubles - because you own the infrastructure.
The People Behind the Build
Veteran professionals. Real experience.
No junior analysts running your deployment. The people who designed the system are the people who build yours.
Fran Horvath
CO-FOUNDER & CMO / CHIEF VISION OFFICER
Strategic operations, financial architecture and AI governance design. Owns the deployment framework and the business case that survives a CFO's scrutiny.
Anwesh Rath
CO-FOUNDER · CTO & CHIEF SCIENTIST
Architects and builds the entire platform end to end - sovereign model stacks, on-prem inference, and the tamper-evident governance layer that lets an enterprise cryptographically prove what its AI actually did. His work spans model-integrity seals, verifiable inference lineage, and output-provenance monitoring - turning "trust us" compliance into receipts you can independently verify. He leads the research and engineering that keeps every AI Standards deployment sovereign, auditable, and impossible to quietly tamper with.
Questions for Enterprise AI Leaders
The things worth asking out loud.
Strategy
"Will the AI strategy you signed off on still be standing in three years - powered, affordable, and actually worth what you're paying for it?"
Power Risk
"When your AI vendor's data center can't get enough power to keep your models running, do you have a Plan B - or just their apology email?"
Grid Competition
"Your AI vendor is bidding against your own employees' homes for electricity. Who loses that auction first - the data center, or the neighborhood?"
Environmental
"Can you put your name on an AI strategy that's quietly burning more natural gas than your last three manufacturing plants combined?"
Cost
"You budgeted $2M for AI this year. What happens to that number when your usage doubles and your vendor's per-token price doesn't move?"
Output Quality
"If your engineers spend more time fixing what the AI got wrong than doing it themselves, is that AI - or is it overhead?"
Get Started
Ready to ask the hard questions?
A 45-minute discovery call. No pitch deck. Just the right questions about your AI strategy - and you deciding if you like the answers.