Managed AI employees
A digital employee that already knows how you work.
We install one job, coach you on the workflow, monitor it, and send a weekly time and value report. You keep the rules. We keep the system running.
The problem
ChatGPT does not know your prices, your exceptions, or which leads you actually want. A generic chatbot guesses. A managed AI employee owns one recurring job with your real context.
How we work
Step 1
Assess the bottleneck
We pick one recurring job that leaks time or revenue: inbound replies, quotes, follow-up, or a process that lives in one person's head.
Step 2
Structure the knowledge
We map inboxes, Drive, CRM, and the person who just knows. You do not clean the mess first. Approved facts become the source the employee runs on.
Step 3
Install one job
We build, host, and monitor the employee. You see the output and a Friday report of tasks, hours saved, and a dollar estimate.
What you get
- One bounded job, not a vague 'AI for the business' project
- Your knowledge stays yours. We install and monitor
- Weekly time and dollar report to decide if it stays
- No new software. Your team works the same way
Questions
- What is a managed AI employee?
- A digital worker that owns one recurring job using your prices, SOPs, and exceptions. We install, coach, monitor, and send a weekly time and value report.
- Do we need to clean up our files first?
- No. The $999 assessment maps inboxes, Drive, CRM, and the person who just knows. We structure the job before we automate it.
- Is our data safe?
- Your knowledge base is yours. Access is limited to the job. Nothing is shared across clients. You can revoke access any time.
- How is this different from hiring someone to do AI?
- A hire learns on your payroll. You own the rules. We own uptime, coaching, and the weekly report.
- Who is this for?
- Small businesses with one recurring bottleneck and sources they can share. If a Zap or Claude Project is enough, we will say so.
