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§ Agent · Outreach

The Outreach data agent that acts the way you would.

It keeps an eye on your Outreach data alongside your CRM and pipeline, on a schedule you set or whenever fresh data lands. When something needs attention, it tells you, or handles it the way you'd want.

D
DefiniteAPP9:14 AM · #pipeline-alerts
⚠️ Sequence reply rate dropped 41% this week; 3 reps below 2% across 1,200 prospects

Reply rates on your top-of-funnel sequences fell from 6.8% to 4.0% over the last 7 days. Three reps are running sequences with reply rates under 2%, well below your team baseline. 1,200 active prospects are in those sequences right now.

Review & approve Dismiss
Outreach Sequences + Emails + Sales Reps · joined to CRM pipeline · audit log

How an agent works

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.

◄ repeats on the schedule you set ►

You stay in control

An agent does what you'd do, and only what you've authorized.

The same trusted numbers

It acts on the same governed metrics as your dashboards, and every action is logged and traceable.

You approve anything that writes

It alerts and recommends on its own; anything that changes data is yours to approve.

Try it on a test channel first

Point a new agent at a throwaway channel and watch its judgment before it touches anything real.

No false alarms

It remembers what it already flagged and waits before acting again, so it won't alert you about the same thing twice.

What you can put an agent on

PipelineACROSS YOUR SOURCES

Tie sequence activity to the pipeline it actually produces

It joins your Outreach sequences and engagement events to the deals in your CRM, so you see which sequences are generating pipeline and which are burning prospects. You reconcile outbound effort to revenue instead of reporting on opens and replies in a vacuum.

SequenceEngagement EventDeal
Sequences

Catch the sequence that stopped working before the quarter does

When a sequence's reply rate or meeting-booked rate breaks its trend, it tells you which steps dropped, which reps are affected, and how many active prospects are in the blast radius. You adjust the cadence while there are still prospects left to reach.

SequenceEmailPerson
Rep Activity

Surface the rep who's falling behind before the pipeline gap shows

It watches each rep's activity mix (emails, calls, tasks completed) against team baselines and flags when someone's volume or outcomes diverge from the norm. You coach the rep this week instead of diagnosing a missed quarter after the fact.

Sales RepCallTaskEmail
Custom

Run any Python it needs to get the job done

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.

Why not just build it yourself?

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:

  • The cross-source join: not one tool's data, but it reconciled against the rest of your stack
  • A trusted, consistent metric: the same number your dashboards use
  • The investigation into why, when something fires
  • A full audit trail of everything it did
  • The upkeep, when the schema drifts or the script breaks at 2am

The data it works from

Every Outreach object, modeled and query-ready the moment you connect.

Deal
revenue_financesales
Person
customermarketing
Company
customersales
Sequence
marketingproduct
Email
marketing
Call
salesengagement
Task
revenue_financesales
Engagement Event
salesmarketing
Sales Rep
customersales

It runs on your real Outreach instance (bounced emails, skipped steps, paused sequences and all), not a tidy demo.

Where it acts

Slack

A message in the channel you choose, with the context and a button to act on it.

Email

A summary in the inbox of the people who need to see it.

Webhook

A payload to your own systems, to wire the agent into whatever you already run.

Warehouse write-back

A flag written back to your warehouse for everything downstream to pick up.

Hand off to Fi

Kick the question to Fi to investigate the why and propose the fix.

MCP

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.

Build your agents with Fi

Fi is your AI analyst. It helps you build and customize everything in Definite, including the agents that watch and act.

Fi

Your AI analyst. Ask questions in plain English, and let it help you build and customize everything in Definite, including your agents.

Meet Fi →

Agents

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 →

Get started

  1. 1Connect Outreach, and the sources it needs to reconcile against. Synced and modeled in an afternoon.
  2. 2See the numbers tie out to what you already trust.
  3. 3Put an agent on one thing you can't afford to miss. Fi helps you build it.
§ FAQ

Common questions

You set the schedule, and it also re-checks whenever fresh Outreach data lands. Each agent watches the one thing you point it at, nothing else.
It alerts and recommends on its own. Anything that writes, whether to a tool, your warehouse, or a customer, is yours to approve. You can also point a new agent at a test channel first and watch its judgment before it touches anything real.
When something fires, it can hand off to Fi to investigate, drilling into the data it has across your connected sources to find what's behind the move, and showing its work.
Those report on Outreach activity in isolation, when you ask. This watches continuously, reasons across Outreach plus your CRM and revenue data, and hands off to Fi to investigate why a sequence is underperforming, so you catch the trend before it costs you pipeline.

Your answer engine
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