Team
operators who want AI work delivered, not configured
Automation only helps if someone keeps it working after week one.
Rebotify runs the AI employee for you: prompts, tools, monitoring, and tuning.
Your team gets the work cleared, not another system to babysit.
Send the work your team keeps debugging. Mia maps what Rebotify can run and tune for you.
Workday pressure
Mia does not score AI interest.
She scores the queue: what piles up, who gets chased, and what still needs approval.
The first version must clear visible work.
Team
operators who want AI work delivered, not configured
Workday sentence
They say: diy agent platforms need a team to babysit them, inbox triage and reply drafting.
Answer that pressure first.
Where it gets stuck
DIY agent platforms need a team to babysit them: Zapier, Make, n8n, Lindy dashboards eat headcount.
Every prompt tweak, every API change, every edge case lands on your team.
That is not a platform — it is outsourced staff you still manage.
What cannot go wrong
You want to build your own agents in-house and own every prompt and integration.
What stays human
You approve every sensitive decision: Customer-facing, legal, financial, and unusual actions wait in the queue for a named human to sign off.
First useful version
The team approves work and reviews metrics — nobody on payroll is debugging prompts.
Work first
The question is simple.
Can this work be cleared with less cost, less waiting, fewer misses, and less manager attention?
Work to clear
The team approves work and reviews metrics — nobody on payroll is debugging prompts.
Impact
To first drafts in the approval queue.
Current cost
Zapier, Make, n8n, Lindy dashboards eat headcount.
Every prompt tweak, every API change, every edge case lands on your team.
That is not a platform — it is outsourced staff you still manage.
Human approval
You approve every sensitive decision: Customer-facing, legal, financial, and unusual actions wait in the queue for a named human to sign off.
Work in motion
Three week-one outputs. Drafted for review before send.
EXAMPLE · 01
The operator runs the morning queue, your team approves what goes out, and weekly tuning closes the loop on missed categories.
EXAMPLE · 02
Contracts, invoices, or applications get a first-pass review inside the operator-managed playbook; humans review only the flags.
EXAMPLE · 03
Numbers, narrative, and call-outs prepared by the AI employee; the operator tunes the report template as the business changes.
48-hour build
We scope the workflow, wire it to your tools, and deploy a working AI role within two business days.
No weeks of planning.
No discovery tax.
We go live and tune in place.
Each week we review what the AI did, what it missed, and what changed in your process.
Edge cases become rules.
New fields, policy shifts, and tool updates get handled the same week.
The AI runs every day.
We watch for errors, stalled queues, and upstream changes.
You see a summary; we own the fix.
Human approvals stay in the queue where you set them.
Flat monthly, per-completed-task, or by outcome.
You pick the model that matches the work.
No minimum term.
Cancel any month.
Send us the bottleneck and rough volume to scope the workflow and confirm the price.
Human control
Customer-facing, legal, financial, and unusual actions wait in the queue for a named human to sign off.
The AI employee gets only the permissions its job needs.
Access can be revoked any day, same day.
Your data and prompts stay private to your tenant.
Tuning happens inside the engagement, not in a shared pool.
Do not start here if
A good first week looks like
Mia checks the cost, risk, what needs sign-off, and whether an AI employee can clear the first version.
If this is cheaper or safer with a person, the scorecard says that.
WORK + APPROVAL SCORECARD
A short check for cost, speed, quality, risk, and the first safe version.
Work
Replies, reports, checks, handoffs, document chases, approvals, or follow-up that keeps coming back.
Cost
Staff time, manager attention, customer wait time, rework, missed follow-ups, or lost revenue.
Quality
Better drafts, faster turnaround, fewer errors, cleaner handoffs, and less chasing from managers.
Control
Customer promises, pricing, refunds, legal language, financial decisions, or anything that can damage trust.
Output: work to clear, current cost, what needs sign-off, pricing options, and the smallest useful test.
Managed AI is a role we run for you.
We scope the workflow, wire your tools, run the operating loop every day, and tune based on what actually happened.
You review results and approve sensitive decisions.
No software to configure.
No prompts to debug.
Managed AI is best for operators who want AI work delivered, not configured with repeated work, a clear human owner, and enough examples to show Mia what good work looks like.
Rebotify finds the stuck task, connects the minimum tools, and puts useful drafts, checks, or summaries into a human approval queue.
Yes.
Rebotify normally starts with human approval for customer-facing, financial, legal, or policy-sensitive actions.
The AI employee prepares the work and escalates uncertainty.
Related pages
Browse all servicesAI consulting
Managed AI for accountants
CRM workflow automation
AI customer service
Send the work your team keeps debugging.
Mia maps what Rebotify can run and tune for you.