Your 'Enterprise Q3 Outbound' sequence fell from 8.2% reply rate to 4.6% starting Wednesday, coinciding with a bounce rate spike on your sales-team-3@… mailbox. 812 prospects hit that step and got no response. Two other sequences sharing that account are trending the same way.
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 Reply.io campaign and prospect data to your CRM, so you see which sequences are actually producing pipeline and which are generating replies that go nowhere. When outreach volume and deal creation diverge, you find out while you can still adjust the sequence, not when the pipeline review reveals the gap.
When bounce rates spike or delivery drops on a sending account, it tells you which sequences and how many prospects are affected. You find out the day the mailbox starts failing, not two weeks later when the reply rate collapse shows up in the weekly report.
It watches reply rates, opt-outs, and engagement across every active sequence. When a campaign that used to convert goes flat, it flags which steps dropped, which prospect segments are underperforming, and whether the template or the list is the likely cause, so you retool the right thing instead of guessing.
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 Reply Io object, modeled and query-ready the moment you connect.
It runs on your real Reply.io account (paused sequences, stale prospect lists, shared mailboxes with mixed sending reputations, 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 →