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§ Agent · Shopify

The Shopify data agent that acts the way you would.

It keeps an eye on your Shopify orders and revenue alongside your books, payouts, and inventory, 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 · #store-finance
⚠️ Shopify revenue and the bank are $9,400 apart for May

Net sales booked in Shopify came in $9,400 above what actually settled to your account, mostly refunds and a payout still in transit, well outside your usual sub-$1,000 swing.

Review & approve Dismiss
Shopify Order + Payment Transaction · reconciled to QuickBooks and your bank · 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 Shopify sales to the bank and your books

It reconciles the orders and payouts in Shopify against your accounting and bank data, and flags the gaps before close, so the revenue you report matches the cash that actually landed. You stop chasing a discrepancy you found a week too late.

OrderPayment TransactionCustomer
Inventory

Catch a stockout before it costs you the sale

When a product that's still selling drops below the cover you set, it tells you which SKU, which location, and how much revenue is exposed at your current sell-through. You reorder on the real number instead of finding out when the listing goes dark.

Inventory ItemProductLocation
Checkout

Watch abandoned checkouts for a revenue leak

When recovered-checkout revenue slips or abandonment breaks its trend, it surfaces the dollars walking out the door and which step they're stalling at. You see the leak while you can still act on it, not in next month's recap.

Abandoned CheckoutOrder
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 Shopify object, modeled and query-ready the moment you connect.

Customer
customerrevenue_finance
Order
revenue_financecustomer
Payment Transaction
revenue_finance
Product
productrevenue_finance
Collection
productmarketing
Inventory Item
operationsrevenue_finance
Location
operations
Abandoned Checkout
revenue_financemarketingengagement
Custom Metadata
general_data_storageproductcustomerengagement

It runs on your real Shopify store (refunds, partial fulfillments, test orders, and custom metafields 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 Shopify, 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 Shopify 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.