Over the last 30 days, your 3-part welcome sequence converted 312 subscribers at $18.40 blended CAC. Your weekly promo campaigns converted 74 subscribers at $61.20 blended CAC, reconciled against Stripe revenue.
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 Mailchimp campaign clicks and conversions against your CRM and payment data, so you see which sends actually drove revenue, not just opens. When the CFO asks for blended CAC by channel, email has a real number.
When your bounce rate climbs or unsubscribe velocity breaks its trend, it tells you which campaigns triggered the spike, how many subscribers you lost, and what segment they came from, so you can fix the content or the targeting before your sender reputation takes a hit.
It watches open rates, click rates, and delivery metrics across every campaign. When a sequence that used to perform well drops below its own baseline, it flags the shift with the numbers and the affected audience segments, so you know where to look.
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 Mailchimp object, modeled and query-ready the moment you connect.
It runs on your real Mailchimp account (test sends, suppressed contacts, messy tags 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 →