FBA fee adjustments hit 14 SKUs last week, concentrated in your top 5 ASINs by revenue. Your books still show last month's cost basis. Combined with 6 refund events totaling $3,200 that haven't reconciled, your actual contribution margin is running $31,600 below what the P&L reflects.
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 Amazon order financials, fees, refunds, and adjustments against your accounting and bank data, and flags the gaps before close. The revenue on your P&L matches what Amazon actually settled, so you never explain a margin discrepancy you found too late.
It watches your FBA inventory positions against sales velocity by SKU. When a product is burning through stock faster than your inbound lead time, it flags the ASIN, the projected days of supply, and the revenue at risk, so you reorder before the listing goes inactive and your organic rank drops.
When Amazon adjusts FBA fees, referral rates, or refund charges, it calculates the dollar impact per SKU against your historical cost basis and flags the ASINs where your contribution margin moved. You find out the week it changes, not when the quarterly P&L looks wrong.
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 Amazon Selling Partner (SP) object, modeled and query-ready the moment you connect.
It runs on your real Seller Central account (FBA fee adjustments, partial refunds, multi-marketplace currency 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 →