Northwind opened 9 chats in the last two weeks (your baseline is ~2), three flagged frustration, and their renewal lands in 58 days. They're not in this week's CSM call list yet.
An agent watches one thing and acts on it. Not a workflow, just a standing watch that usually does nothing and acts the moment it should.
An agent does what you'd do, and only what you've authorized.
It acts on the same governed metrics as your dashboards, and every action is logged and traceable.
It alerts and recommends on its own; anything that changes data is yours to approve.
Point a new agent at a throwaway channel and watch its judgment before it touches anything real.
It remembers what it already flagged and waits before acting again, so it won't alert you about the same thing twice.
It joins your Zendesk Chat conversations to the account, ARR, and renewal date in your CRM, so a spike in chats from an account renewing next month surfaces as a ranked call list, not a number nobody connected. You catch the slide while there's still time to act on it, instead of finding out at the renewal.
When chat volume breaks its trend, or a department's missed-chat and wait-time numbers drift past where you'd want them, it tells you which accounts and agents are affected before it shows up in a CSAT report. You see the coverage gap the day it opens, not at the end of the quarter.
It watches whether your triggers and shortcuts are doing what you set them up to do, and flags it when conversations stop matching the rules you built, so a silent routing break doesn't quietly bury the accounts you most need eyes on. You find out the automation slipped before a week of chats lands on the wrong queue.
Beyond alerts and write-backs, an agent can run arbitrary Python, so it can do whatever the task actually requires: call an API, push a call list to your CS tool, reshape the data, or wire into your own tooling. The action space is yours to define.
You could rig one of these with a cron job and a Slack webhook in an afternoon. The watching is the easy part. Here's what you'd own forever, and don't, here:
Every Zendesk Chat object, modeled and query-ready the moment you connect.
It runs on your real Zendesk Chat data (bot sessions, banned visitors, half-finished conversations and all), not a tidy demo.
A message in the channel you choose, with the context and a button to act on it.
A summary in the inbox of the people who need to see it.
A payload to your own systems, to wire the agent into whatever you already run.
A flag written back to your warehouse for everything downstream to pick up.
Kick the question to Fi to investigate the why and propose the fix.
Expose it to your own agents and tools over MCP, and drive it from your stack.
Run it in your own VPC or fully self-hosted. Everything it does is pure SQL and Python you can inspect.
Fi is your AI analyst. It helps you build and customize everything in Definite, including the agents that watch and act.
Your AI analyst. Ask questions in plain English, and let it help you build and customize everything in Definite, including your agents.
Meet Fi →The watchers and actors. Once you've built one, it runs on its own, keeping an eye on what matters and acting the way you would.
Autonomous agents →