Slack logo
§ Agent · Slack

The Slack data agent that acts the way you would.

It watches your Slack channels alongside your product usage and billing data, on a schedule you set or whenever fresh data lands. When a conversation signals churn risk or expansion opportunity, it tells you, or handles it the way you would.

D
DefiniteAPP9:14 AM · #cs-alerts
⚠️ 3 accounts going quiet in support channels, $47k ARR at risk before Q3 renewal

Message volume from Oakmont, Ridgeline, and Praxis dropped 60%+ over the last 14 days in their dedicated channels. All three have Q3 renewals. Thread response times from their teams also spiked from ~2 hours to 18+ hours, well outside their 4-hour baseline.

Review & assign CSMs Dismiss
Slack Messages + Threads · joined to Stripe Subscriptions + product usage logs · 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

Churn signalACROSS YOUR SOURCES

Spot the silence before it becomes a cancellation

It joins your Slack conversation and message data with product usage and billing, so when an account's channel goes quiet while their usage is dropping, you find out weeks before the renewal. Not from a stale spreadsheet health score, but from the actual pattern across systems.

MessageConversationMembership
Escalation routing

Route escalations to the right CSM with full context

When a thread in a customer channel crosses your response-time threshold or carries frustration signals, it flags the thread, pulls in the account context from your CRM and billing data, and routes it to the CSM who owns that account. No more scanning channels manually every morning.

ThreadMessageReaction
Engagement scoring

Turn channel activity into a health score that stays current

It tracks message volume, reaction patterns, thread depth, and response latency per customer channel, then scores engagement weekly so your team knows which accounts are thriving and which need a call. The score updates itself; nobody has to maintain the spreadsheet.

MessageReactionThreadUser
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 Slack object, modeled and query-ready the moment you connect.

Conversation
engagementoperations
User
engagementoperations
Message
engagementoperations
Thread
engagementoperations
Reaction
engagement
Membership
engagementoperations

It runs on your real Slack workspace (archived channels, bot noise, one-word replies 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 Slack, 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 Slack 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.

Your answer engine
is one afternoon away.

Book a 30-minute call and watch us build your first dashboard live, with your own data.