Most companies spend more on AI than it saves them.

Partly, and the honest version of that answer is the one worth having.

We can prove what the system touched: leads worked, response time before and after, quotes out same day, hours no longer spent retyping at your real cost, deals closed where the system ran follow up. All timestamped.

We cannot prove your revenue moved because of us. Nobody can. Your market and your pricing moved the same quarter too. Anyone who puts their logo on your revenue chart is selling a coincidence.

So the deal is this: we write the baseline before we build, the system reports the numbers it can stand behind to you rather than through us, and you keep the report if you fire us.

We know. Most people who call us have. MIT studied three hundred deployments and found roughly ninety five percent produce nothing measurable, almost never because of the model, because the tool got bolted on instead of wired in. The same study found buying from a specialist worked about twice as often as building it internally, roughly sixty seven percent against roughly a third. You did not fail at AI. You did the version that mostly does not work.

Source: MIT NANDA, The GenAI Divide: State of AI in Business 2025.

It will break. Everything breaks, and we will not promise otherwise. What we promise: you will know the moment it breaks, see what it touched, and put it back. Alerts, a readable audit log, a documented rollback and a change window, all in writing before you sign.

The code lives in your repository, on your cloud accounts, on your API keys. Documentation is written so a stranger could pick it up. The engagement is month to month with thirty days notice, and the exit handover is in the contract, not billed later. If you fire us, everything keeps running. Build it for a client and the same terms travel with them, not just with you.

Start with what we control. We classify your data before anything gets wired, service accounts get the least access that will do the job, production data does not go into prompts by default, and your team gets a written acceptable use policy, all logged where you can read it.

Then read the vendor contract, not the marketing. Anthropic's commercial terms, as one example, say Anthropic may not train on your content and you retain all rights to inputs and outputs. Other vendors say different things. We read the one you pick with you before anything is chosen.

This team has worked on some of the most complex security controls that exist, including FISMA High, one of the federal government's highest security certifications for technology. We have also been directly involved in some of the largest hacks and security incidents of the last twenty years, including the SolarWinds attack, where we did forensic analysis and recovery work in the aftermath. Of everything on this page, this is the part least likely to get done badly here.

Two answers. It is built to be run by somebody who is not an engineer: flip a toggle instead of filing a ticket. And you do not have to. We keep the control layer switched on for a monthly fee covering monitoring, the audit log and a scheduled change window. The retainer runs $1,500 to $3,500 a month depending on how much is running.