§ 01 — The Founding
The gap between the dashboard and the failure.
Years ago, Dave Tyson and Sandra Estok built enterprise cybersecurity teams together. They knew how organizations defended themselves when the threats were known. Then their paths separated for years, and each of them learned something different the hard way.
Dave sat on the buyer's side of the tools that promise to manage risk, and watched the distance between what a dashboard reports and how an organization actually fails. Sandra went from IT to cybersecurity to building companies, and arrived at governed AI systems as the speed of the work changed underneath her.
When they came back together, they were looking at the same problem from two sides: organizations are adopting AI faster than their oversight can follow. ARQ Lab is what they decided to do about it — instruments that make forming risk examinable while it is still a pathway rather than a loss.
§ 02 — What we are for
Why ARQ Lab exists.
AI adoption governed by deliberate choices, never by surprise.
Close the gap between the speed at which AI failures form and the speed at which people can examine them.
Before impact, forming risk is still a decision. We build instruments that help you examine declared exposure against stated tolerance, and AI systems designed to operate within the limits you set.
§ 03 — The People
The lab behind the instruments.
Sandra Estok
CofounderSandra is the architect. Her career layers into the AI work — IT, then cybersecurity, then entrepreneurship, now governed AI systems — and every layer shows in how she builds: multi-model development environments where independent reviewers check the work that goes through a gate, and the one who produced it is never the one who signs it off.
MBA · GIAC-GSLC · CIPM · aC|CISO · TEDx speaker · GCRAI Ambassador
"I've never been able to build technology this fast."
Dave Tyson
CofounderDave has built and led private sector multi-national security and technology businesses across North America, Europe, and Asia.
He spent three decades in enterprise security leadership, including chief information security officer roles, across technology, energy and consumer goods and has served on numerous fiduciary and industry boards.
He has evaluated risk-management tools from the buyer's side, and what he saw there — the distance between what a dashboard reports and how an organization actually fails — is what he decided to do something about.
ARQ Lab, LLC (arqlab.ai), Wichita Falls, Texas.
§ 04 — A private briefing
Govern exposure. Defend tolerance.
ARQ Lab builds the instruments that make AI risk examinable, so you can decide before impact instead of explaining after it.
§ 05 — The quotient
ARQ — the Artificial Risk Quotient
Our mark is a Q. It has always stood for Quotient.
What we hear from executives —
We're spending millions on AI, but when the board asks what our actual exposure is, nobody has a straight answer. We don't need another 50-page compliance framework, and we don't need a lecture on how LLMs work. We need to know if the autonomous systems we deployed yesterday are going to cost us our margins tomorrow. We're flying blind at a thousand miles an hour — and the damage won't always show up as a regulatory fine. It'll show up as a bad quarter.
That is why we built ARQ Lab around the Artificial Risk Quotient.
In environmental science, a risk quotient is the ratio between measured exposure and acceptable tolerance. Applied to AI, it is a discipline for understanding exactly what you are carrying.
The quotient isn't a single score we calculate for you — it is the thesis that guides everything we build. We provide the instruments to examine your declared exposure against your stated tolerance, moving the conversation beyond compliance and into operational reality.
Exposure
what you have declared you are carrying
Tolerance
the limit you have chosen
Your line. Are you over it?
We give you both numbers and the evidence behind them. Where the line sits is your decision, and your board's. The mark is how you see it.