Stock for 14 high-velocity SKUs dropped below your reorder threshold this week, concentrated in your East Coast and Midwest fulfillment centers. At current sell-through rates, 6 of those SKUs will stock out within 4 days. Your top supplier's average lead time is 9 days, well past the window.
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 Veeqo inventory positions across warehouses to your order velocity and supplier lead times, so you see which SKUs are burning down faster than replenishment can cover. You walk into the ops review with a stockout risk list grounded in days-of-supply and revenue exposure, not just unit counts on a screen.
When order-to-ship times for a warehouse or shipping method break their trend, it tells you which orders are aging, how much revenue is waiting, and where the bottleneck is forming. You hear about it while you can still reallocate, not after delivery promises start slipping.
It watches order volume and AOV by channel against their baselines, and flags when a channel's performance moves in a way that changes your fulfillment mix or margin. A marketplace channel doubling its volume overnight is an ops problem if your warehouse staffing assumed last month's split.
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 Veeqo object, modeled and query-ready the moment you connect.
It runs on your real Veeqo account (oversold SKUs, partial shipments, stale warehouse counts 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 →