TikTok reports 340 conversions on those campaigns, but joining to CRM pipeline, zero closed deals trace back. Combined spend hit $13,300 over seven days against a $4,200/wk baseline for that objective. The rest of the account is holding at target.
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 TikTok Ads spend and conversion events to CRM pipeline and billing data, so you see true CAC and ROAS by campaign, not TikTok's view-through and click-through counts in isolation. You stop reporting on platform-attributed conversions that never show up as closed deals.
When CPM spikes, CTR drops, or ROAS slips below your line, it tells you which campaigns and ad groups are drifting, how much spend is at risk, and what changed. You find out mid-flight, not when the monthly spend report lands.
When frequency climbs and engagement decays on the ad that was carrying the account, it surfaces the affected creatives and audiences alongside the dollar impact, so you swap the asset before performance craters. The watching happens daily, not whenever someone remembers to open TikTok Ads Manager.
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 TikTok Ads object, modeled and query-ready the moment you connect.
It runs on your real TikTok Ads account (paused campaigns, attribution-window mismatches, test creatives 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 →