How to Create AI Assistants Over Your Business Data
Off-the-shelf AI does not know your business. This video shows how to build AI assistants that run over your own data and slot into a process you already have, using the m-Power Development Platform. The example plugs AI into the workflow that fires after a support ticket is submitted, so routing, context, and guidance happen automatically.
What you'll learn
This video adds AI assistants to a support workflow that triggers the moment a ticket is submitted. Here is what you'll see them do, and how they get built:
Classify every ticket automatically
Each ticket gets sorted by priority, type, and customer tone, so an urgent problem never sits in the same queue as general feedback.
Route to the right rep without a manager
Assignments consider skills, workload, and ticket type, so the work lands with the right person and no one has to triage by hand.
Policy-based playbook for each ticket
The assistant recommends how to handle each ticket from your rules, giving newer team members a guide to follow instead of guesswork.
Controlled data access per assistant
Tool functions decide exactly what an assistant can reach, such as support staff, workloads, and documentation, so it works within its lane.
Define the prompt and the fields it returns
Simple prompts tell the assistant what to do, and named fields set what it hands back, like the assignee or a set of suggested actions.
Write results back to your database
The assistant's output lands in your data, so it shows up automatically on the ticket page and in the applications your team already uses.
See what AI assistants could do in your workflow
We'll walk through m-Power live, using your data and your use case, and answer any questions your team has.