Reply rates on your top-of-funnel sequences fell from 6.8% to 4.0% over the last 7 days. Three reps are running sequences with reply rates under 2%, well below your team baseline. 1,200 active prospects are in those sequences right now.
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 Outreach sequences and engagement events to the deals in your CRM, so you see which sequences are generating pipeline and which are burning prospects. You reconcile outbound effort to revenue instead of reporting on opens and replies in a vacuum.
When a sequence's reply rate or meeting-booked rate breaks its trend, it tells you which steps dropped, which reps are affected, and how many active prospects are in the blast radius. You adjust the cadence while there are still prospects left to reach.
It watches each rep's activity mix (emails, calls, tasks completed) against team baselines and flags when someone's volume or outcomes diverge from the norm. You coach the rep this week instead of diagnosing a missed quarter after the fact.
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 Outreach object, modeled and query-ready the moment you connect.
It runs on your real Outreach instance (bounced emails, skipped steps, paused sequences 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 →