These deals have close dates inside 4 weeks but no Zoom meetings or participant activity since early June, well past your ~5-day meeting cadence on late-stage opportunities.
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 Zoom meetings and participant data to the pipeline in your CRM, so you see which commit-stage deals have gone quiet on calls and which reps are carrying a full calendar but not advancing anything. You catch the gap before the forecast slips, not when you're reconciling the quarter.
When your webinar registration-to-attendance rate drops below its trend, it tells you which events, which sources, and how many registrants fell off, and surfaces the absentee list so you can route follow-up before the leads go cold.
It watches poll response rates, Q&A volume, and session duration across your meetings and webinars, and flags the events where participation dropped off. You know which sessions landed and which ones lost the room, without scrubbing through reports host by host.
Beyond alerts and write-backs, an agent can run arbitrary Python, so it can do whatever the task actually requires: call an API, kick off a job, 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 Zoom object, modeled and query-ready the moment you connect.
It runs on your real Zoom account (recurring meetings that nobody deletes, test webinars mixed in with production, hosts who forget to enable registration, 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 →