Contacts completing your onboarding automation are converting to Deals at 6.2% vs. your 10.5% trailing average. 83 scored contacts cleared MQL threshold but have no Deal created, mostly from the webinar campaign that ran two weeks ago.
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 ActiveCampaign automations and lead scores to your deal pipeline and payment data, and flags where the funnel leaks before your weekly review. You see which campaigns produced revenue and which just produced contacts, without stitching three tools together by hand.
When a Deal sits in a stage too long or loses its next Sales Activity, it tells you which ones are stalling and how much pipeline is at risk. You steer reps off one view instead of cross-referencing deal stages and task logs yourself each week.
When open rates, click rates, or bounce rates break their trend on a campaign, it surfaces which Audience Segments are affected, how engagement shifted, and whether the list health explains it, so you fix deliverability before it compounds.
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 ActiveCampaign object, modeled and query-ready the moment you connect.
It runs on your real ActiveCampaign account (half-tagged contacts, stale automations, test campaigns 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 →