Give us the job. Any job. We design, build, integrate and deploy a custom AI employee that actually does the work, inside the systems you already run.
Free 30-minute AI Employee Design Call. No deck, no pitch. We map the job.
Six examples of what we've built. Yours will be someone else entirely.
Anyone can make an AI answer a question on a stage. Holding a real position is a different discipline entirely.
That distance, between something that answers and something that holds a position, is the entire job. It is what we build, and it is the only thing we charge for.
These six are examples, not a menu. They're the roles we get asked for most often. Every employee we build is designed from scratch around your business, your systems and your workflows. If you can describe the job, we can build the employee that does it.
You don't pick a role from a list. You describe the job.
AI the job you need done Employee
The title is whatever the job is. There is no catalogue to fit you into.
Whatever outcome you need held, the position gets designed around it: any title, any task, any system you already run. If the work is repetitive, digital and performed through software, an employee can almost certainly hold it. If it can't, you'll hear that on the first call rather than after you've paid us.
Book a Call →The same nine steps every time. It is a hiring process, not a software project, which is why it produces something that survives contact with your business.
What must this employee actually accomplish, and what is it worth when it happens?
How is the work done today: every step, every decision, every exception.
What information and tools the role requires, and how we reach them safely.
What it may do alone, what needs a human, and what it must never touch.
The employee gets made. Reasoning where judgement is needed, deterministic code where it isn't.
Scored against realistic work before it touches a customer. It passes or it doesn't ship.
Deployed under supervision, earning autonomy one class of work at a time.
Approved responsibilities graduate to independent operation. Exceptions still escalate.
Measured monthly, improved continuously, promoted when it earns it.
Nobody hands a new hire the company chequebook on day one. The same judgement applies here. Every employee we deploy climbs a ladder, and it only climbs when the numbers say it should.
You decide the pace. If an employee never leaves supervised mode because you're not comfortable, that is a perfectly good outcome. It is still doing the work, you're just signing it off.
Watches the work happen. Acts on nothing. Builds the ground truth we test against.
Proposes every action. A human sends it. You see exactly how it thinks.
Acts alone on low-risk work. Anything above the line still needs approval.
Holds its approved responsibilities independently. Exceptions escalate to a named human.
Move the sliders to match the job you have in mind. This is your arithmetic, not ours. We've made no assumptions you can't see and change.
An estimate built entirely from the numbers you entered above. It is a planning tool, not a promise. The real figure depends on your volumes, your systems and how much of the role genuinely automates. We'd rather tell you it's a bad idea than sell you a bad one.
CustomEmployees.ai came out of a distribution business, not a consultancy. The method exists because the first versions of it were built to fix real operational problems, with real customers on the other end and real consequences for getting it wrong.
That background is the whole product. We know where these systems break, what permissions they actually need, how legacy software fights back, and how to tell the difference between an employee that works and a demo that got lucky. Those scars are the methodology.
That's your decision, not ours, and we'd encourage you not to lead with it. What we sell is capacity, coverage and consistency: the same team handling several times the volume, every lead followed up, every invoice chased, a response at 2am. Most clients redeploy people onto work that actually needs a human rather than cutting headcount. If the economics eventually change what your org chart looks like, that's a business decision you'll make with better information than you have today.
We'll tell you, on the first call, before you've paid anything. If the work is repetitive, digital, rules-and-judgement based and performed through software, there's a good chance an AI employee can hold meaningful parts of it. If it depends on physical presence, relationships that can't be delegated, constantly shifting undocumented rules, or data we can't reach, we'll say so. A no from us is worth more than a yes from someone who bills either way.
An authority matrix written before a line of code exists. Every action the employee could take is classified as autonomous, requires-approval, or forbidden. The forbidden ones are enforced in code, not requested in a prompt. Issuing refunds, changing bank details, deleting records, negotiating outside set limits: these are structurally unavailable to the employee, not merely discouraged. On top of that: a probation period, escalation rules, an audit trail of every action, and spending limits.
Whichever produces the most reliable employee for your job, and we'll tell you exactly what we picked and why. We're not a reseller for any model provider, so we have no reason to force one into a role it's wrong for. Model choice is an implementation decision we make on evidence and revisit when better options appear. What you're buying is the job being done, not a particular vendor's logo.
For a Starter role, typically two to four weeks to deployment, then a three-week probation before full autonomy. Professional builds run four to eight weeks depending on how many systems are involved and how cooperative they are. The honest variable is almost never the AI. It's how quickly we can get credentialed access to your systems and a decision-maker who can answer questions about edge cases.
Two models, agreed before development starts, never after. In managed employment, we own and operate the infrastructure and you pay to employ the worker. That is the common choice, and the cheaper one. In an owned deployment, you take the code and run it on your infrastructure; that costs substantially more and the IP boundaries are written into the agreement up front. Your data is always yours in both.
Monitoring and incident response, model and usage costs, integration maintenance when your systems change underneath us, failure review on anything that went wrong, new training for edge cases the employee hasn't met before, small workflow improvements, security updates, and a written monthly performance review. An AI employee left unattended degrades. Your systems change, your policies change, edge cases accumulate. The monthly fee is what keeps it employed rather than merely installed.
A 30-minute design call. We map the role, the systems and the arithmetic, and you get an honest answer either way.