Call volume for these accounts fell 60% over the past two weeks against their 90-day baseline. Cross-referenced with your CRM; 3 are mid-contract renewals worth a combined $87,400 ARR. CSM outreach list attached.
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 RingCentral call and message history to your CRM pipeline, computes a communication-frequency baseline per account, and flags the ones going quiet. You get a ranked at-risk list with renewal dates and dollar exposure, not a dashboard you have to remember to check.
It tracks call volume, talk time, and missed-call rates per rep and per account using the extension-level call log and contact directory. When coverage gaps appear, it surfaces them so you can re-balance the book before an account slips through.
It measures inbound-to-response time across calls, SMS, and voicemail using the message store and call log. When response times drift above your team's baseline for a segment or a rep, it flags the trend and the accounts affected so you can coach before it costs a renewal.
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 RingCentral object, modeled and query-ready the moment you connect.
It runs on your real RingCentral account (missed calls, abandoned voicemails, test extensions 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 →