# Adopt AI without breaking what already works. Twenty-five years of systems work underneath every decision. The principal you hire is on every engagement. [Start with a fixed-scope assessment](/ai-readiness-audit) --- ## Most firms sell first and assess the risk later. I work the other way around. Your team is already using AI. The question is whether anyone has checked what those tools can reach, what data they hold, and what happens the day one of them goes down. I answer that question before you spend a dollar on the answer. What runs, what it touches, what could break, and what to do next. In writing, with real numbers, from the person actually doing the work. I take on funded consumer brands between Series Seed and Series C. Founders who have something worth protecting and know that speed without judgment is how you break it. --- ## Four things I do. Each one starts with what you can afford to lose. ### AI Adoption Adopt what makes your team better. Skip what just makes the budget bigger. Most of what gets sold as AI right now is software looking for a problem. I sort the real opportunities from the noise, then build the ones worth building with guardrails your team can actually follow. [AI Adoption](/ai-adoption) ### AI Risk and Governance Know what your AI is doing with your data before a funder, a client, or a regulator asks. I map what your tools can reach, where your exposure is, and what needs to change first. This is where the AI Readiness Audit lives. [AI Risk and Governance](/ai-risk-and-governance) ### Security and Infrastructure The credibility floor underneath everything else. Networks, identity, cloud, hardening. If you have not had a real security assessment in the last twelve months, you are guessing, and I will tell you exactly where. [Security and Infrastructure](/security-and-infrastructure) ### Custom Software Websites, internal tools, integrations, and one-off builds that do not fit a product category. The common thread is not the technology. It is the judgment about whether to build the thing at all, build it simply, or leave it alone. [Custom Software](/custom-software) --- ## The hardest thing I run is not a client engagement. It is Advo360. Advo360 is my production case management platform for victim services organizations. An environment with zero tolerance for a data handling mistake, holding the most dangerous information in a survivor's life. It runs single-tenant in each client's own cloud account, their data in a place they own, fully portable by design. If the security posture and the discipline hold up there, applying that same standard to your customer data is not a stretch. It is the floor. Advo360 founder Jeff Thomas designed and delivered the [MrBallen Foundation](https://mrballen.foundation/) Tech Education Series for the Foundation's network of victim services organizations. The Foundation has added both Cybertek and Advo360 to its partner referral network. --- ## Three things that actually happened. ### Somebody finally read the invoice A forty-person nonprofit was paying for enterprise Microsoft licensing and nobody could say why. Someone picked the plan years earlier, the invoices kept coming, and everyone assumed enterprise meant safer. I audited what they actually used. They were on Office 365 E3 at roughly nine dollars a seat, and here is the part nobody caught: that enterprise plan did not include endpoint protection or email threat defense at all. They had been paying enterprise prices for a plan that left the front door open. I moved all forty seats to Business Premium at five-fifty nonprofit pricing. It covered every workload they had and added the security their enterprise plan never included: Defender EDR, Safe Links and Safe Attachments, Conditional Access. Ten seats were free under Microsoft's nonprofit grant, so they were paying for thirty. They went from about forty-three hundred dollars a year to roughly two thousand. Less money, and protected for the first time. That is what happens when someone reads the invoice with your interests in mind instead of the vendor's. ### The data everyone said was gone I was hired to recover a failed database for a victim services organization. The data was as corrupt as anything I had seen in twenty-five years of this work, and the vendor's system was unrecoverable. The judgment call was to stop trying to save the software and rescue the data instead. I extracted all of it, then spent six months beside an advocate manager with nearly two decades in the field until the replacement did the work instead of the staff. That rebuild became a platform. That organization still runs on it today. Anyone can execute a migration. Knowing when to declare the old system dead, and proving nothing gets left behind, is the judgment you are actually hiring. ### The six-figure contract they did not sign A funded brand came to me ready to sign an enterprise AI contract. Per-seat pricing, usage fees, annual escalators. I ran their actual use case first: internal documents and repeatable workflows, nothing that needed a frontier model on tap for every employee. An in-house deployment on their own infrastructure handled it. One build, no per-seat meter, their data never leaving their environment. Full transparency, that build was my contract and I got paid to do it. They still came out tens of thousands of dollars ahead of what the subscription would have cost over its life, and they own the result instead of renting it. Enterprise AI vendors are betting you will never do that math. I do it before you spend a dollar. --- ## You do not need a finished plan. You need to stop guessing. Start with a fixed-scope assessment. Four to six weeks, one fixed fee, the principal on every hour. What you get at the end is an operating plan, not a shopping list. [Start with a fixed-scope assessment](/ai-readiness-audit)