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§ Agent · Intercom

The Intercom data agent that acts the way you would.

It keeps an eye on your Intercom conversations alongside product usage and revenue, on a schedule you set or whenever fresh data lands. When an account is sliding toward churn, it tells you, or lines up the outreach the way you'd want.

D
DefiniteAPP9:14 AM · #cs-risk
⚠️ Northwind's renewal is at risk: support load up, usage down

Northwind opened 9 conversations in 14 days (3x their baseline), CSAT slipped to 2 of 5, and weekly active seats dropped 40%, with a $48k renewal landing in 31 days.

Review & approve Dismiss
Intercom Conversation + Contact + Company · joined to product usage and ARR · 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

RiskACROSS YOUR SOURCES

Rank the accounts heading for churn, before the renewal

It joins your Intercom conversation volume, CSAT, and tags to product usage and ARR, then ranks the accounts whose support pattern says trouble is coming. You get a weekly call list ranked by risk and dollar exposure, not a quarterly dashboard you read after the logo is already gone.

ConversationContactCompany
Spike

Catch a support spike on a named account in time to act

When one company's conversation volume breaks its trend, it tells you who, how far above baseline, and which tags are driving it, then hands off to Fi to dig into what changed. You hear about the account that's quietly melting down before the CSM does, while there's still room to save it.

ConversationCompanyTag
Load

See where the support load is really landing

It watches conversation volume and resolution patterns by team, segment, and tag, and flags when a queue or a customer segment is drifting out of line with the rest. You catch the staffing gap or the broken release that's generating tickets before it becomes a satisfaction problem.

ConversationTeamSegment
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 Intercom object, modeled and query-ready the moment you connect.

Contact
customermarketingsupport
Company
customersupport
Conversation
supportengagement
Segment
marketingsupportcustomer
Tag
supportoperations
Team
supportoperations
Admin
supportoperations

It runs on your real Intercom workspace (test conversations, untagged threads, bots 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 Intercom, 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 Intercom 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.
Fin answers your customers inside the inbox. This watches your conversation data alongside product usage and revenue, ranks the accounts at risk by dollar exposure, and hands off to Fi to investigate why, so you find the churn signal before the renewal, not after.

Your answer engine
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