Realis Solutions Group · Approach
With you, from the boardroom to the courtroom.
Every recommendation we make is built to be stood behind — by us, alongside you — whether it lands in front of your board, your regulator, an insurer, or a courtroom. That standard changes how advice gets built: evidence first, named owners, decisions you can show your work on.
The 3/3/3 model
Assess in days. Pilot in weeks. Prove value in months. It's the delivery model the industry's largest technology platforms are standardizing on — and it's how every Realis engagement is built for you.
A short, scored diagnostic — the AI Readiness Assessment — that tells you exactly where you stand and what to do first. No six-month scoping exercise, no discovery theater. You leave with a posture you can report and a prioritized list you can act on.
A focused second engagement, scoped from what the assessment surfaced — executive advisory, a development-lifecycle or product evaluation, a vendor decision, or a leadership workshop. Fixed scope, principal-led, evidence out the other side.
Production value you can point to: controls in place, decisions made, exposure reduced, and the fiscal impact measured. Custom engagements come third — only when the work has earned them.
Decisions, not dashboards
Clarity + Protection = Velocity
A boutique, on purpose
What we're not
What we are: senior advisors at the intersection of AI, security, and enterprise risk — turning your uncertainty into clarity and confidence.
The independence test
Ask who in the relationship loses money if the honest recommendation is to spend less, cancel an initiative, or leave an existing arrangement in place. If the answer is the party giving the advice, the advice is not independent — however competent and well-intentioned the people giving it are.
— Machine Speed, Human Judgment, Realis executive strategy paper, July 2026
The practical version: stop asking one relationship to both deliver the work and grade it. Send the operational work to the best available operator and hold them to outcome-based commitments — then put the judgment about whether those commitments are being met somewhere that has no revenue riding on the answer. That's the seat we take.
It's the test we hold ourselves to. We don't resell tools, operate your SOC, or build the AI we assess — which is what makes "spend less," "wait," and "you're fine, here's what to maintain" answers we're actually free to give.
One caution we hold ourselves to just as hard: judgment without operational literacy is theater. An advisor who can't interrogate a mean-time-to-respond figure or tell the difference between an AI agent that closed a ticket and one that resolved an incident produces governance documents and no risk reduction. The judgment layer earns its position by being credible about operations — not by being distant from them.
Two disciplines, one firm
The value of Realis is the intersection: data science and AI security meets management and emerging technology.
Fifteen years in applied AI research and AI security — national AI policy engagement, standards work with NIST, MITRE, OWASP, and ISACA, and the architect of a global cloud AI security practice.
Three decades of management and emerging technology — present at the industry's pivotal launches, translating what's next into frameworks organizations actually act on.
Any question. 20 minutes. A real answer — no pitch. Tell us what you want to know when you book, and we'll come ready.