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§ Agent · ShipHero

The ShipHero data agent that acts the way you would.

It watches your ShipHero fulfillment data alongside your accounting and sales channels, 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
⚠️ Fulfillment cost per order up 19% this month; $8,400 in shipping overcharges unreconciled

Carrier rate increases hit 3 of your top 5 SKUs by volume last week. 34 shipments billed at expedited rates that were booked as ground. Your books still reflect last month's per-unit shipping cost, putting actual COGS $8,400 above what the P&L shows.

Review & approve Dismiss
ShipHero Shipments + Orders · reconciled to QuickBooks · 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 fulfillment costs to the books and the bank

It reconciles your ShipHero shipping charges, pick-and-pack fees, and order totals against your accounting and bank data, and flags the gaps before close. The COGS on your P&L matches what fulfillment actually cost, so you never explain a margin discrepancy you found too late.

OrderShipment
Inventory

Catch a stockout before it kills your sales velocity

It watches your warehouse inventory positions against order velocity by SKU. When a product is burning through stock faster than your purchase order lead time, it flags the SKU, the projected days of supply, and the revenue at risk, so you reorder before you lose the sale.

InventoryProductPurchase Order
Returns

Surface a return spike with the reason and the cost

When your return rate moves on a SKU or product line, it surfaces the reason codes, the refund impact, and the pattern behind it. You find out the week it changes, not when the quarterly write-down hits the books.

ReturnOrderProduct
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 ShipHero object, modeled and query-ready the moment you connect.

Order
revenue_financecustomer
Product
marketingsupport
Inventory
revenue_financeproduct
Shipment
revenue_financemarketing
Return
revenue_financecustomer
Vendor
revenue_financecustomer
Purchase Order
revenue_financeengagement

It runs on your real ShipHero account (partial shipments, return reason codes, multi-warehouse splits, 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 ShipHero, 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 ShipHero 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.