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§ Agent · Zuora

The Zuora data agent that acts the way you would.

It keeps an eye on your Zuora data alongside your accounting and bank, 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 · #finance-alerts
⚠️ Billed revenue diverged from cash collected by $47,300 this period

Invoice totals for the month are $1.23M, but payments applied only reach $1.18M. The gap traces to 14 invoices with partial payments and 6 with failed collection attempts, up from your ~$12K/period baseline.

Review & approve Dismiss
Zuora Invoices + Payments + Refunds · reconciled to NetSuite · 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 Zuora billings to the bank and your books

It reconciles your Zuora invoices and payments against your accounting system and bank data, and flags the gaps before close, so the revenue on your board deck matches the cash that actually landed. You never find out about a collection shortfall from your auditor.

InvoicePaymentRefund
Churn

Catch subscription churn before it compounds

When cancellations or downgrades break their trend, it tells you which subscriptions are affected and how much ARR is at risk, surfaces the rate plans losing volume, and lines up the retention action for you to approve before the next renewal cycle closes.

SubscriptionProduct CatalogCustomer Account
Usage

Flag a usage-to-billing mismatch before the invoice goes out

For usage-based charges, it compares metered consumption against what the billing engine calculated, surfaces accounts where the gap is material, and routes the discrepancy to the right person before the invoice is finalized.

UsageInvoiceSubscription
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 Zuora object, modeled and query-ready the moment you connect.

Customer Account
customerrevenue_finance
Subscription
revenue_financecustomer
Product Catalog
revenue_financeproduct
Invoice
revenue_finance
Payment
revenue_finance
Refund
revenue_finance
Usage
revenue_financeproduct

It runs on your real Zuora tenant (amendments, voided invoices, mid-cycle proration adjustments 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 Zuora, 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 Zuora 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 operate inside Zuora's own walls, when you ask. This watches continuously, reasons across Zuora plus your GL and bank, and hands off to Fi to investigate why, so you catch the gap before close, not after.

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