4 people marked terminated in Workday over 14 days ago still have active Okta accounts, 2 with admin on production apps, none caught by your offboarding runbook.
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 Okta users and app assignments to your HR system and flags anyone marked terminated who still has live access, before the next access review (or a breach) finds it for you. You see exactly which apps and which admin grants are still open, with the offboarding action lined up to approve.
It watches application assignments against the last-login signal and your billing data, then surfaces the paid seats sitting idle so you can reclaim them. You stop renewing licenses for people who haven't signed in since onboarding.
When someone lands in a privileged group they shouldn't be in, or a group balloons past its usual size, it tells you who changed and when. You catch the over-grant the moment it happens instead of reconstructing it from logs a quarter later.
Beyond alerts and write-backs, an agent can run arbitrary Python, so it can do whatever the task actually requires: call the Okta API, open a deprovisioning ticket, 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 Okta object, modeled and query-ready the moment you connect.
It runs on your real Okta org (service accounts, deactivated-but-not-deleted users, half-migrated app assignments 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 →