
Case Study
Hundreds of orders a day, processed without a single person touching them
How Erazor Bits, a wholesale apparel and glassware company, went from manual order processing to a fully autonomous fulfillment pipeline, saving 5 hours a day and over $100,000 a year in labor costs.
5 hrs/day
Saved through end-to-end automation
$100K+/yr
Saved on labor costs
5,000+
Products managed across multiple warehouses
0 humans
Required in the daily order-to-ship pipeline
The Problem
A growing wholesale operation held together by manual work
Erazor Bits designs, produces, and distributes custom silk-screened apparel and glassware — military, firefighter, EMS, law enforcement, and patriotic-themed products sold to retailers across the United States. Founded in 1993 in New Jersey, the company had built a strong brand and a catalog of over 5,000 products.
When CEO Khalid Shehady decided to expand into drop-shipping, the operational complexity multiplied overnight. Orders now flowed in from multiple channels: the company website, Amazon, and Shopify. Each source had its own format, its own quirks, and its own data structure.
Staff had to match incoming orders to the correct item and size variant, figure out which warehouse held the inventory, calculate shipping rates, generate packing slips and labels, and create invoices — all by hand, for hundreds of orders every day. Khalid was also moving his family to Aruba, meaning the entire operation needed to be cloud-based and manageable from thousands of miles away.
Orders arrived from multiple channels (website, Amazon, Shopify) in different formats, requiring manual consolidation and data entry
Every order required manual item matching, size variant lookup, warehouse assignment, shipping calculation, and invoice creation
The process needed three full-time employees' worth of labor just to keep up with daily volume
The owner was relocating internationally and needed the entire operation to run autonomously in the cloud
The Solution
A fully autonomous order-to-ship pipeline. Zero human intervention required.
We built a complete end-to-end automation system that handles every step of Erazor Bits' fulfillment process, from the moment an order is placed on any channel to the moment a tracking number is emailed to the customer. The system runs every day, processing hundreds of orders completely on its own.
Multi-Channel Order Import & Validation
Orders are automatically imported from the website, Amazon, and Shopify. The system validates the data, resolves item and size variant matching (S, M, L, XL, etc.), and flags any discrepancies. No manual review needed for clean orders.
Intelligent Box Splitting & Shipping Logic
Orders are automatically split into shipping boxes based on item quantities and product type (t-shirts, long sleeves, sweaters, glassware, each with different packing requirements). The system selects the correct shipping method and rate based on box weight and destination, and assigns the appropriate warehouse based on inventory location. Multi-warehouse orders are split automatically.
ShipStation Integration
Shipping batches are sent directly to ShipStation. Tracking numbers, tracking summaries, and shipping labels are pulled back into the system automatically. Invoices are generated the moment an order is marked as shipped. No manual step required.
Warehouse Print & Pack
Print batches generate barcode labels and packing slips that are sent directly to warehouse printers. The warehouse crew picks, packs, and ships. That's the only human touchpoint in the entire process.
Automated Inventory Reordering
The system tracks quantity on hand, reserved, on sales order, on purchase order, and on backorder, with configurable reorder points, preferred restock levels, and reorder tiers. Reorder decisions are informed by recent sales data (3, 6, 9, and 12-month windows). When stock hits a threshold, purchase orders are automatically generated and emailed to vendors for approval.
Backorder Management
When inventory is short, the system automatically creates backorders and notifies users. In-stock items ship immediately while backordered items are tracked separately until stock arrives.
Supporting infrastructure: Supporting infrastructure includes custom item fields (location, aisle, bin number, part number, category, product type, materials, color, UPC, weight, image URLs, size extensions), barcode generators, custom print templates, custom email templates, return label generation, and a QOH change log for full inventory auditability.
The Results
A one-person operation running what used to take three
The automation eliminated approximately five hours of manual work every single day. Tasks that previously required three full-time employees now run autonomously — Khalid manages the entire operation himself, from Aruba, with the warehouse team handling only the physical pick-and-pack.
The financial impact was equally dramatic. By removing the need for dedicated order processing staff, Erazor Bits saved over $100,000 annually in labor costs. Those savings weren't just cost reduction — they were redeployed into growing the product line and expanding the business.
Every day, hundreds of orders flow in from three sales channels, get validated, matched to the correct items and sizes, split into the right boxes, assigned to the right warehouses, shipped through ShipStation with correct rates and tracking, invoiced, and confirmed — all without a single person intervening. For a founder who needed to run a complex wholesale operation from a different continent, this wasn't an optimization project — it was a fundamental reinvention of how the business operates.
“What I do on a daily basis would require three people to do… and I do it myself.”
Related Insights
5 Signs Your Manufacturing Operation Has Outgrown Its Software
If your team is doing manual workarounds every day, the problem isn't your people — it's your software. Here are five signs you've outgrown off-the-shelf tools.
The Real Cost of Disconnected Systems in Distribution and Fulfillment
When your CRM, inventory, and order management don't talk to each other, the hidden costs compound daily. Here's how to quantify the drag — and what connected looks like.
What to Expect from a Custom Software Engagement (And How to Not Get Burned)
Most bad custom software projects fail in discovery, not development. Here's what a good engagement looks like from first call to go-live — and the red flags to watch for.
Still processing orders the hard way?
If your team is spending hours on tasks that should run themselves, let's talk about what full-process automation could look like for your operation.
Book a Free AI + Ops Review →