Message volume from Oakmont, Ridgeline, and Praxis dropped 60%+ over the last 14 days in their dedicated channels. All three have Q3 renewals. Thread response times from their teams also spiked from ~2 hours to 18+ hours, well outside their 4-hour baseline.
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 Slack conversation and message data with product usage and billing, so when an account's channel goes quiet while their usage is dropping, you find out weeks before the renewal. Not from a stale spreadsheet health score, but from the actual pattern across systems.
When a thread in a customer channel crosses your response-time threshold or carries frustration signals, it flags the thread, pulls in the account context from your CRM and billing data, and routes it to the CSM who owns that account. No more scanning channels manually every morning.
It tracks message volume, reaction patterns, thread depth, and response latency per customer channel, then scores engagement weekly so your team knows which accounts are thriving and which need a call. The score updates itself; nobody has to maintain the spreadsheet.
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 Slack object, modeled and query-ready the moment you connect.
It runs on your real Slack workspace (archived channels, bot noise, one-word replies 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 →