Your top three nurture campaigns generated 410 new prospects last month but only 12 reached opportunity stage, down from a 9% baseline. Visitor activity on those prospects dropped 58% after initial form fill, suggesting the nurture sequence is stalling before sales picks up.
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 Pardot campaign touches and prospect activity against the opportunities and closed revenue in your CRM, so you see which campaigns actually influenced pipeline and which ones just generated form fills. When your blended CAC drifts because a high-spend campaign stops producing pipeline, you hear about it before the board review.
When open rates, click events, or visitor activity on a segment start decaying below your baseline, it tells you which campaigns, lists, and prospect cohorts are affected, how far engagement has fallen, and how many prospects are stalling. You rework the sequence before the leads go stale and sales blames marketing for dead pipeline.
It watches the relationship between your Pardot prospect scores and actual conversion to opportunity over time. When high-scored prospects stop converting at their historical rate, it surfaces which scoring criteria drifted and which segments are over- or under-valued, so you recalibrate before sales wastes cycles on the wrong leads.
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 Pardot object, modeled and query-ready the moment you connect.
It runs on your real Pardot account (stale lists, orphaned prospects, scoring models nobody recalibrated, and Salesforce sync conflicts), 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 →