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§ Agent · Freshsales

The Freshsales data agent that acts the way you would.

It keeps an eye on your Freshsales pipeline alongside your outreach channels and revenue, on a schedule you set or whenever fresh data lands. When a deal or number needs attention, it tells you, or handles it the way you'd want.

D
DefiniteAPP9:14 AM · #pipeline-alerts
⚠️ Win rate dropped 11 pts this month; 6 deals stuck in Proposal for 14+ days, $218K at risk

Your 90-day win rate fell from 34% to 23%, driven by 6 open Deals that have sat in Proposal stage for 14+ days with no logged Activity, well past your ~5-day stage cadence. Combined value is $218K and 3 have close dates inside two weeks.

Review & approve Dismiss
Freshsales Deals + Activities + Contacts · reconciled to revenue in your billing system · 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

ReconcileACROSS YOUR SOURCES

Tie your pipeline numbers to the revenue that actually closed

It joins your Freshsales Deals and win/loss data to the invoices and payments in your billing system, so the pipeline number your team presents ties out to the revenue that actually landed. When the two drift, it flags the gap and tells you which records are off before you present a forecast built on stale data.

DealAccount
Stalled deals

Catch the deals going quiet before the close date slips

When a Deal sits in a stage too long or has no recent Activity logged against it, it flags the record, tells you how long it has been stalled relative to your normal cadence, and lines up the next step for you to approve. The forecast you present is built on deals that are actually moving.

DealActivity
Coverage

Spot the Accounts that need a touch before they cool

It watches your Accounts and Contacts for gaps in coverage: the Account with no open Deal, the Contact whose last Activity was weeks ago, the segment with thinning pipeline. You see which parts of the book need work before the quarter gets away from you.

AccountContactActivity
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 Freshsales object, modeled and query-ready the moment you connect.

Deal
revenue_financesales
Contact
customermarketing
Account
revenue_financecustomer
Activity
customersales

It runs on your real Freshsales account (lost deals, stale contacts, half-filled accounts 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 Freshsales, 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 Freshsales 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 score leads and surface insights inside Freshsales, when you look. This watches continuously, reasons across your pipeline plus the billing and outreach data that validate it, and hands off to Fi to investigate why a segment is stalling, so you find out before the quarter closes, not after.

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