The revenue column in your Ops KPI spreadsheet shows $218k for last week, but Stripe plus QuickBooks shows $244k for the same period. The gap opened three weeks ago when someone hardcoded a filter. 4 other sheets reference this number downstream.
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 the numbers in your Google Sheets to the systems they were pulled from, and flags when a sheet has drifted from the source of truth. You find out before someone builds a deck on a stale export, not after the board meeting.
When a manually maintained spreadsheet goes quiet, it tells you which one, how long it has been stale, and what downstream reports depend on it. You hear about it while there is still time to refresh, not when someone asks why last month's numbers are in this month's report.
When a column header changes, a new tab appears, or rows shift in a way that breaks the expected structure, it surfaces exactly what moved and what queries or dashboards downstream would break. You catch the structural change before your pipeline does.
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 Google Sheets object, modeled and query-ready the moment you connect.
It runs on your real Google Sheets (the merged cells, the inconsistent headers, the blank rows someone left in, the tabs named 'Sheet2 (old copy)'), 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 →