Inbox and follow-up triage
Reads customer emails, drafts replies, pulls context from CRM records, and queues anything sensitive for approval before it sends.
Rebotify designs, builds, and runs a managed AI employee for one recurring business workflow. We start with the work you would hire for tomorrow, wire it into your tools, and get the first useful drafts in the approval queue within 48 hours.
Mia is our AI employee. Email her — she’ll book your 15-minute call. That’s the demo.
The best AI automation projects do not begin with a blank chatbot. They begin with a recurring queue, a messy handoff, or a manual review loop that already costs the team hours every week.
Reads customer emails, drafts replies, pulls context from CRM records, and queues anything sensitive for approval before it sends.
Classifies issues, drafts first responses, spots stale knowledge, and escalates edge cases with the context already attached.
Collects weekly numbers, explains movement, flags anomalies, and turns messy updates into a report your team can approve.
Researches accounts, prepares outreach, keeps follow-ups moving, and updates pipeline notes without adding another dashboard.
Compares files against a playbook, highlights missing clauses, drafts summaries, and routes exceptions to the right reviewer.
Tracks who owes what, nudges the right person, prepares the decision packet, and keeps the workflow moving without manual babysitting.
Most AI automation projects hand over a tool. Rebotify owns the operational loop: the workflow design, the integrations, the approvals, the memory, and the weekly tuning that keeps the employee useful.
01
We pick one recurring workflow, define the judgment points, identify the systems involved, and write the first operating playbook.
02
We wire email, Slack, CRM, documents, or internal systems through a controlled gateway so the AI employee can work inside the real process.
03
Drafts, summaries, decisions, and escalations appear where your team already works. Customer-facing actions pause for human approval.
04
We monitor failures, update prompts and memory, add edge cases to the playbook, and improve the employee like an operator, not a software vendor.
COMMON AGENCY PROJECT
The build works in the sales call, then your team inherits the prompts, integrations, errors, and exception handling. The automation exists, but no one owns its performance.
REBOTIFY MODEL
The employee has a defined job, a review queue, tool permissions, memory, escalation rules, and a team behind it. We keep tuning it after the first drafts ship.
Rebotify is run from Melbourne and works with businesses operating across Australia, New Zealand, the United States, and the United Kingdom. For Australian teams, that means the person mapping your workflow understands local compliance conversations, approval culture, and the practical gap between a promising AI demo and a workflow that survives Monday morning.
Human approvals for customer-facing work
Tool access scoped to the workflow
Weekly monitoring and improvement after launch
The same service pattern applies across service, operations, legal, sales, and customer teams: pick the repeated judgment loop, build the employee around it, and keep humans in the approval path until trust is earned.
An enrolment workflow where the AI employee reads student context, drafts the next best reply, and escalates policy-sensitive cases.
A first-line service workflow that triages repetitive issues while keeping humans in control of customer-facing decisions.
Document assembly and review workflows where the employee checks source files, prepares summaries, and flags exceptions before review.
Mia is our AI employee. Email her — she’ll book your 15-minute call. That’s the demo.