Your team is already using AI. Who is watching it?
Managed AI Security controls what your people can access, monitors what actually goes into the models, and keeps your policies enforced month after month. Run the way we have run managed networks and security for decades.
Vibe coded something that actually works? Let's make it real.
Here is a pattern we keep seeing, and honestly, we love it. A CEO, a CTO, a CMO, or another key leader gets an idea, sits down with AI, and vibe codes a proof of concept. No dev team, no budget cycle, just an idea and a chat window. And it works.
Then it stalls. The whole thing lives in a chat history and a OneDrive folder. No version control, no permissions, no secure way to put it in front of customers or staff. It runs on one laptop and nowhere else. That last stretch, from working prototype to secure system, is where most of these ideas quietly die.
This is work we are doing with clients right now. We come alongside you and carry it over the goal line: out of chat and OneDrive, into GitHub with real version control, built out with professional tools like Claude Code, wrapped in real permissions, and put behind a secure internet front end so the people who need it can actually use it.
Your idea stays your idea. We make sure it survives contact with the real world.
Bring us your proof of conceptNobody has settled on a name for this yet. We call it what it is.
Every AI tool an employee opens is a new door in and out of your business. Data walks out through prompts. Answers walk back in and get acted on. Most companies have no idea which doors are open, who is walking through them, or what they are carrying.
Networks got this treatment decades ago. Somebody decides who gets access, watches the traffic, and keeps the rules enforced as things change. That discipline is called managed services, and it is the reason your network is not the wild west. AI inside most businesses today is the wild west.
Managed AI Security is that same discipline applied to AI: access under control, usage visible, policy enforced, continuously. Not a one-time policy document. Not a training day. An ongoing service with somebody accountable for it.
We are not waiting for the category to get a name. We are already running this with customers.
Three jobs, done continuously.
The working parts.
Scope depends on your size, your tools, and your risk surface. These are the components we build it from.
We can build agents to watch your agents.
AI employees are here. Agents that read and send email, work tickets, talk to customers, and run workflows. They work at machine speed, around the clock, and no human is going to review all of that by hand.
So we supervise them the same way: with monitoring agents built for the job. An agent that watches what your AI does, checks it against the rules you set, and flags what a human actually needs to see. Oversight that runs at the same speed as the thing it is overseeing.
We built an agent that monitors an AI employee's email communications. Every message it sends gets watched, not assumed to be fine.
This is a security shop extending into AI. Not the other way around.
tekRESCUE runs an active MSP and cybersecurity practice. We monitor networks, enforce policy, and deal with real attacks for real businesses every week. Managed AI Security is that same operation pointed at a new surface, run by the same people, with the same accountability.
If you want the full picture of how we think about AI and security, read our AI + Security manifesto.
Where this stands, honestly.
The tooling in this space is young and moving fast. We will tell you that to your face, because we would rather you hear it from us than find out later.
The security vendors are catching up to the problem, and the controls get better every quarter. So we build with what actually works today, and we tighten the screws as the tools mature. That is what managed means: the service keeps improving without you having to re-buy it.
Credit where it is due: Microsoft has built serious AI governance and control into the Copilot ecosystem, and on that front they are ahead of nearly everyone. The catch is that those controls mostly help if your team actually lives in Copilot, and in our experience most teams do not want to. Our job is covering the AI your people actually use, whatever mix that turns out to be.
Get eyes on your AI before something walks out the door.
Managed AI Security is scoped during the AI Profit and Growth Assessment, like everything else we do. We walk through your business, your tools, and your risk surface. You walk out with a roadmap you can actually use.