The cohort that signed up this week is completing the core action far less often than your trailing baseline, and it is concentrated in self-serve accounts on the latest app version.
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 watches your Amplitude usage next to billing plan and account data, so you find out which accounts are leaning on the product hard enough to upgrade, before the renewal conversation, not after. The usage signal and the revenue context live in one place, which is the join Amplitude can't make on its own.
When a new cohort completes the core action less often than your baseline, it tells you which flow and which segment, then hands off to Fi to dig into why across the events you've tracked. You hear about a broken onboarding step this week, not in next month's funnel review.
When daily or weekly active users slip below trend, or session activity falls off in a segment that used to be sticky, it surfaces the move and the accounts behind it. You catch the disengagement early, while there's still time to act on it.
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 Amplitude object, modeled and query-ready the moment you connect.
It runs on your real Amplitude project (untracked events, renamed properties, cohorts you set up months ago 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 →