Client Story · Hercules Candy

Every morning, someone printed the orders and checked the weather.

Hercules Candy has made candy by hand for 120 years, with techniques passed down through generations of one family. Their order review was almost as traditional: hundreds of orders a week — thousands in the busy months — each one checked by hand against the weather, the carriers, and the candy inside the box. We connected their systems and turned their judgment into rules, and left the final say exactly where it belongs.

The Pegasus order review queue: every order listed with customer, destination, shipping method, cold packs, and review flags
120
Years of candy made by hand — and counting
<1 hr
Busy-day order review — down from several hours
2,100+
Orders processed in the first ten weeks
4 of 5
Recommendations approved without changes — and climbing

The problem

The decisions lived in people's heads

Each order meant a tour: find it in Shopify, identify the candy and where it was headed, look up arrival-day temperatures on weather.com, compare FedEx and UPS for the fastest and cheapest service, work out cold packs from the candy type and transit time — then update ShipStation and print the label. Hundreds of times a week. Thousands in the busy months.

FIVE SYSTEMS

A tour for every order

Shopify to weather.com to the carrier sites to ShipStation — every order crossed four or five tools before a label printed, and none of them talked to each other.

JUDGMENT CALLS

Rules nobody wrote down

How many cold packs for boiled candy versus chocolate, in July, going to Texas? The answers lived in experienced heads — and the weather kept moving after every decision was made.

ONE AT A TIME

Refunds & upgrades by hand

A shipping upgrade meant manually calculating the cost difference, emailing the customer, and sending an invoice — all separate steps. Refunds worked the same way, one order at a time.

The old morning
  1. Print the day's orders
  2. Check each one in Shopify — candy type, destination
  3. Look up arrival-day temperatures on weather.com
  4. Compare FedEx & UPS for the fastest, cheapest service
  5. Work out cold packs from candy type and transit time
  6. Update ShipStation and print the label
Several hours on busy days
The new morning
  1. Open the queue — every order already reviewed
  2. Scan the recommendations and the reasoning
  3. Change anything you disagree with
  4. Print — that's the approval
Under an hour

What we built

Their judgment, turned into a system

We connected the systems they already used — Shopify, ShipStation, the carriers, the weather — and encoded how they actually made decisions: a rules engine reviews every order against the forecast for its arrival date and live transit times, then queues its recommendation for a human to approve. Nothing was replaced. Everything was connected.

THE ENGINE

Every order, reviewed at 5am

Cold-pack counts, shipping upgrades or cheaper swaps, heat holds, and flags — recommended automatically, with the full "why" attached to every call. Pending orders get re-checked as the forecast moves.

THE QUEUE

Approval built into the workflow

Staff open the morning queue, scan the recommendations, and print the pickslips — and printing is the approval. Disagree with a call? Change it from a dropdown. The team stays in charge; the busywork disappears.

BOUNDED AUTOMATION

Money moves only inside guardrails

Small, clear-cut cold-pack refunds are issued automatically at ship time — capped, audited, with anything ambiguous routed to a person. Hot orders trigger a pay-or-delay upgrade flow the customer confirms themselves.

REFUNDS & UPGRADES

Calculated, emailed, invoiced — in a click

The platform computes the shipping difference or refund automatically; staff review it and send the customer's email or invoice directly from the app, instead of juggling separate steps per order.

TUNABLE RULES

The client owns the logic

Every rule — cold-pack thresholds, product categories, shipping methods — is editable in settings, with an audit trail of every change and a plain-English page showing exactly what the engine will do.

SELF-IMPROVING

The system learns from overrides

When staff consistently override a recommendation the same way, the platform notices and proposes a rule change — which a human reviews and applies. It never changes its own rules.

An order detail in Pegasus: the engine recommends a jumbo cold pack, an upgrade to UPS Next Day Air, and a two-day hold because the arrival forecast reaches 97°F The Pegasus rules page: plain-English, temperature-tiered cold pack rules the client can read and edit

How it runs

A morning that used to take the morning

The platform runs the same rhythm the team always did — it just does the looking-up, cross-checking, and re-checking before anyone sits down. On the busiest days, a review that took several hours now takes less than one.

5:00 AM

The batch runs

New orders are pulled from Shopify and reviewed against each one's arrival-date forecast and live carrier transit times. Every still-pending order is re-checked for forecast drift.

MORNING

Staff work the queue

Each order shows the recommendation and the reasoning. Most get printed — which approves them, moves them to pick & pack, and pushes the confirmed shipping method to ShipStation.

ALL DAY

The platform keeps watch

Fulfillments sync back every few minutes, bounded refunds go out at ship time, paid upgrade invoices release their orders automatically, and anything unusual raises a notification.

MONDAY 5AM

The scoreboard arrives

A weekly email reports every order reviewed, what the engine recommended, and what staff changed — a standing, honest measure of how well the system matches their judgment.

"Pegasus has streamlined our ordering process and eliminated so much manual labor. Our review process has gone from several hours to <1 on average."

— HERCULES CANDY

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