Vendor transactions posted in entity US-002 and US-005 this week don't net to zero against the eliminating entity. 14 vouchers totaling $87,400 are unmatched, up from your typical ~$6,000/wk residual.
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 Dynamics 365 Finance general ledger and vendor transactions against your bank feed and external revenue data, and flags the gaps before close. The numbers on your board deck match the cash that actually landed, across every legal entity.
When vendor invoice aging breaks its trend, it tells you which vendors are affected, how much cash is at risk, and whether the invoices tie back to the right GL accounts. You see the exposure before it surprises you at close.
When postings across your companies don't net correctly, it surfaces the unmatched vouchers, the entities involved, and the dollar impact, so your consolidation is clean before anyone has to ask.
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 Microsoft Dynamics 365 Finance object, modeled and query-ready the moment you connect.
It runs on your real Dynamics 365 Finance environment (partial postings, intercompany residuals, multi-entity quirks 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 →