Organic installs fell from 58% to 46% of total while iOS paid CPI rose to $4.80 (your baseline is ~$3.65). The shift started Thursday after the App Store ranking change. 3 campaigns are above your efficiency ceiling.
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 Adjust install and campaign data to your revenue source, so you can see which networks and creatives drive users who pay, not just users who install. You stop funding channels that look good on installs but never convert to revenue.
When CPI, eCPC, or ROAS breaks its trend on any network or campaign, it tells you which creatives and geos moved, by how much, and whether the shift is worth acting on. You find out in hours, not at the end of the sprint.
When session activity or DAU trends fall for a cohort, it traces the drop back to the campaign and network that acquired those users, so you know whether it is a product problem or an acquisition quality problem.
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 Adjust object, modeled and query-ready the moment you connect.
It runs on your real Adjust data (reattributions, deattributions, organic/paid splits 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 →