Friday's bank deposit was $7,300 less than the settled Square orders for the week. $4,100 traces to held funds on disputed transactions at your Midtown location; the remaining $3,200 is timing on two batches that haven't cleared yet. Your books still show the full amount as received.
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 reconciles your Square orders and payouts against your accounting and bank data, and flags the gaps before close. The revenue on your P&L matches the cash that actually landed, so you never explain a discrepancy you found too late.
When your refund rate breaks its trend, it surfaces which locations, products, and categories are driving it, with the dollar impact and the baseline it moved from. You find out the day it moves, not at month-end close.
It watches inventory counts by location against your sales velocity. When a product is trending toward stockout faster than your reorder lead time, it flags the SKU, the location, and the projected days of supply left, so you reorder before the shelf is empty.
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 Square object, modeled and query-ready the moment you connect.
It runs on your real Square account (voided transactions, multi-location quirks, held funds, 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 →