CASE STUDIES

Numbers we can stand behind.

Three engagements across the operations we automate: customer service, Amazon Vendor Central, and third-party warehousing. Each one measured hours, errors and dollars before and after. Client names are withheld; the full write-ups are downloadable below.

01 — CUSTOMER SERVICE AUTOMATION · BEVERAGE / CPG Customer service as an automated operational intelligence system A fast-growing beverage company shipping hundreds of thousands of orders across Amazon, Walmart, Shopify and DTC.
6–8 hrs DAILY CS WORK · BEFORE
1–2 hrs DAILY CS WORK · AFTER
4–7 hrs RETURNED EVERY DAY
THE PROBLEM

Every ticket meant research across systems: which channel, which order, which policy, which remedy — then documenting it and later mining the pile for recurring product, packaging and carrier issues. The cost wasn't ticket volume. It was the manual work behind every ticket.

WHAT WE BUILT

A custom platform built around the client's real policies, channels and escalation rules. It reads incoming customer mail, identifies the channel and the reason for contact, pulls the order, applies channel-specific policy, resolves within approval limits and escalates what genuinely needs human judgment. Every interaction is logged as structured data — contact reason, channel, order, item, carrier, lot, cost, resolution — feeding a live analysis view by platform, product, lot and financial impact. A claims workflow turns qualifying damage reports into carrier claims using the facts already captured, so recovery stops depending on someone remembering to file.

· Routine interactions handled automatically; exceptions escalated with context · Reporting eliminated as a separate task — the operation creates its own dataset · Eligible carrier claims initiated from case data instead of abandoned
↓ Download the full case study (PDF) Related: Logistics & 3PL →
02 — AMAZON VENDOR CENTRAL · CONSUMER GOODS Stabilizing Vendor Central operations for a growing CPG brand A national CPG brand selling through Amazon Vendor Central. We didn't touch advertising — we managed what happens after Amazon places the order.
20 hrs WEEKLY MANAGEMENT · BEFORE
5 hrs WEEKLY MANAGEMENT · AFTER
75% TIME REDUCTION
THE PROBLEM

Every PO created a chain of downstream requirements — inventory, allocation, packaging, labels, receiving, deductions, reconciliation. The account had become reactive: too many emergencies, too much manual checking, and heavy dependence on one person's institutional knowledge.

WHAT WE BUILT

A structured PO workflow from purchase order through receiving, reconciliation and payment, with controls at the points where money is usually lost. Packaging and labeling treated as operational controls, since a label mistake becomes a deduction. An investigation process that separates vendor errors from Amazon errors by reconstructing what physically shipped against what Amazon received — including a high-risk Andon incident where a potential inventory write-off became a documented escalation instead of an accepted loss.

· Chargebacks and deductions minimized at the source, challenged when eligible · Return-to-Vendor exposure and unnecessary write-offs reduced · One person's knowledge converted into SOPs, checklists and escalation paths
↓ Download the full case study (PDF) Related: Amazon Vendors →
03 — 3PL & WAREHOUSE STANDARDIZATION · MULTI-CHANNEL CPG Turning tribal warehouse knowledge into a documented operating system A multi-channel CPG company fulfilling Amazon, Walmart, DTC and wholesale through third-party warehouses across multiple facilities.
80% FEWER FULFILLMENT ERRORS
85% FEWER SHIPMENT EXCEPTIONS
95% FEWER CHARGEBACKS
THE PROBLEM

Operating knowledge lived in emails, calls and individual employees. The same process ran differently depending on the facility, the person and the day — producing wrong shipments, label mistakes, orders shipping after cancellation, and 10–15 hours a week of management firefighting.

WHAT WE BUILT

The warehouse operation mapped from order creation to shipment completion, then converted into SOPs written against the actual screens employees use — not policy documents in a folder. Channel-specific workflows for Amazon, Walmart, DTC and wholesale; packaging as a fulfillment control; a cancellation procedure that confirms fulfillment actually stopped; defined escalation rules for what falls outside normal parameters.

· 90% less time correcting mistakes; 50% faster employee onboarding · Management oversight down from 10–15 to 3–5 hours a week · A consistent, auditable standard across every facility
↓ Download the full case study (PDF) Related: Trucking & Freight →
Client names are withheld under confidentiality. What we can always show: the working tools themselves, demonstrated live on every process review. measured, not estimated
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