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§ Agent · Zoho Books

The Zoho Books data agent that acts the way you would.

It keeps an eye on your Zoho Books data alongside your billing and bank, on a schedule you set or whenever fresh data lands. When something needs to tie out before close, it tells you, or handles it the way you'd want.

D
DefiniteAPP9:14 AM · #finance-close
⚠️ AR aging jumped: $42,600 past 60 days, up from your $11,000 baseline

9 invoices crossed the 60-day mark this week, concentrated in two accounts. That is nearly 4x your trailing average and worth a collections pass before month-end.

Review & approve Dismiss
Zoho Books Invoices + AR Aging Report + Contacts · joined to bank deposits · 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 booked revenue to billings and the bank

It reconciles the P&L on your Financial Reports against what your Invoices show billed and what actually landed in the bank, and flags the gaps before close, so the revenue on your board deck is a number you can defend. You're never explaining a discrepancy you found too late.

Financial ReportsInvoicesChart of Accounts
AR aging

Catch aging receivables before they slip

When a customer's balance crosses into 60 or 90 days past due, it tells you who, how much, and against which open invoices, and lines up the collections nudge for you to approve, so the cash doesn't quietly age out of reach.

InvoicesContactsCredit Notes
AP & spend

Flag a spend spike before it hits the P&L

It watches your Bills and Expenses against their trailing baselines, and when a vendor or category breaks its pattern, it surfaces the dollar impact and the line items involved so you can approve or push back before the cash goes out.

BillsExpensesVendorsPurchase Orders
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 Zoho Books object, modeled and query-ready the moment you connect.

Invoices
revenue_financesales
Bills
revenue_financeoperations
Contacts
customersales
Vendors
operationsrevenue_finance
Items
productrevenue_finance
Sales Orders
salesrevenue_finance
Estimates
salesrevenue_finance
Purchase Orders
operationsrevenue_finance
Expenses
revenue_financeoperations
Credit Notes
revenue_finance
Journal Entries
revenue_finance
Chart of Accounts
revenue_finance
Financial Reports
revenue_finance
Currencies
revenue_financegeneral_data_storage

It runs on your real Zoho Books org (the manual journal entries, the miscategorized expenses, the multi-currency rounding 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 Zoho Books, 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 Zoho Books 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.
Zia flags anomalies inside Zoho Books, when you look. This watches continuously, reasons across your books plus billing and the bank, and hands off to Fi to investigate why, so the gap surfaces before close, not after.

Your answer engine
is one afternoon away.

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