9 invoices crossed the 60-day mark this week, concentrated in two accounts. That is nearly 4x your trailing average and worth a collections pass before month-end.
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 the P&L on your Financial Reports against what your Invoices show billed and what actually landed in the bank, and flags the gaps before close, so the revenue on your board deck is a number you can defend. You're never explaining a discrepancy you found too late.
When a customer's balance crosses into 60 or 90 days past due, it tells you who, how much, and against which open invoices, and lines up the collections nudge for you to approve, so the cash doesn't quietly age out of reach.
It watches your Bills and Expenses against their trailing baselines, and when a vendor or category breaks its pattern, it surfaces the dollar impact and the line items involved so you can approve or push back before the cash goes out.
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 Zoho Books object, modeled and query-ready the moment you connect.
It runs on your real Zoho Books org (the manual journal entries, the miscategorized expenses, the multi-currency rounding 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 →