AdviceForge is the AI advisory practice I run. It exists to help small-to-mid-market companies get real value from AI by working with their leadership teams on the workflow, data and ownership questions that usually decide whether AI initiatives produce returns.
Most companies have tried AI. Few are getting real value from it. The reason is rarely the model. It is almost always the workflow around the model, the data feeding it, or the ownership inside the company for making AI capability actually stick.
I work as an embedded fractional Chief AI Officer, accountable for outcomes alongside the existing leadership team rather than handing over a deck and leaving. The work is workflow redesign plus building actual AI proficiency across the people doing the work, not a tool deployment dressed up as a strategy.
Better AI use is a discipline, not a purchase. The discipline is harder to design than a tool license but cheaper to ignore.
Licenses purchased and tools opened are not the same as work being done differently. Compute is the cheapest part of the stack and the easiest line item to cut when leadership looks for ROI.
Better prompts cannot save a workflow that was never designed for AI involvement. The work has two layers. Redesign workflows around what AI makes possible. Level up the people doing the work so they move past chatbot-grade use.
If the direction is wrong, more speed makes things worse. If the leadership team is not aligned on what AI should accomplish, no tool deployment can fix that.
They are data, workflow or ownership problems. Outdated data produces wrong recommendations. Undefined workflows resist automation. Unclear ownership produces motion without accountability.
A consultant who hands over a deck and leaves has no skin in whether the recommendations work. A fractional executive who sits in the leadership team week to week is accountable for outcomes alongside the existing team.
AI did not change that. It just made it cheaper to ignore. The companies that succeed treat verification and judgment as core engineering work, not as polish.
These beliefs come from specific kinds of work. Hardware-software integration, high-consequence trading systems and high-reliability infrastructure. The hard part of any consequential automated system is not the model. It is the verification, the override authority and the discipline to clean up the world the system reads from. Those problems are decades old. AI just made them more visible and more urgent.
I am the founder of AdviceForge and serve as a fractional Chief AI Officer for small-to-mid-market companies working to redesign their work around AI rather than just add tools on top of it.
Before AdviceForge, I co-founded Sentry Enterprises in 2018 and served as CEO through December 2025, then continued on the board through 2026. Sentry is a deep tech startup in biometric security, advanced card technology, Web3 payment solutions and digital identity infrastructure. I personally led the integration of AI across Sentry's engineering organization.
Before Sentry, I spent 13 years at CME Group in progressive software engineering and operations leadership roles, including building CME's international technology captive center in Belfast and serving as Managing Director and General Manager for UK and Asia Technology Operations.
I started my career as a software and systems engineer in the United States Air Force, working on military intelligence and space-based satellite imagery platforms. 10+ years in the US Air Force and defense industry before CME.
I have been hands-on with AI tooling since the original GPT betas. Multiple commercial-grade software systems I have designed and built along the way include DexTrader, a trading systems pilot, RelayNet, an AI network communications platform, and AdviceForge, the practice I now run.
I co-host the new Frontier Tech podcast and the AI in the Lab series on LinkedIn Live, both focused on what is actually working at the frontier of AI and what is quietly breaking down. I am based in Charlotte, North Carolina.
The fastest way to start is to email mark@adviceforge.com with a short note about your company and what you are trying to do with AI. I will set up a 30-minute scoping call to understand the situation and figure out whether a fractional engagement is the right next step.
Engagements typically unfold across three phases. A diagnostic that takes a deep dive into your company and workflows and delivers a feasibility-validated roadmap, roughly 30 days. A roadmap activation that drives the first wave of redesign as a bounded 60 to 90 day engagement. An embedded retainer where I sit in the leadership team a few hours a week and execute the roadmap ongoing.
Engagements run onsite or remote depending on what works for the client. Onsite time tends to make leadership reviews and stakeholder conversations sharper, and it is available for any engagement where it adds value. AdviceForge is a practice of Science Brew LLC.
Book a 30-minute call to see whether a fractional engagement fits.
