Wholesale Container & Intermodal Equipment
Reduction in average time from search to completed purchase
Container listings indexed from previously unstructured sources
About
Lummid Containers built an AI-powered marketplace where customers search for shipping containers in natural language and complete the purchase directly on the platform. The catalog is assembled by pulling listings, specs, and pricing from hundreds of unstructured data sources into a single searchable, transactable index.
Industry
Wholesale Container & Intermodal Equipment
Company size
50 – 200 employees
Founded
2000
The Company
One of North America's largest wholesale container networks
Lummid Containers has supplied new, used, and specialty shipping containers — reefers, flat racks, open-tops, and military-specific equipment — for more than two decades, operating out of over 350 container depots and terminals across all 50 states.
Purchasing had always run through a sales rep: a customer would call or email, a rep would check availability across a patchwork of depot spreadsheets, PDFs, and inboxes, and a quote would come back hours or days later. Leadership wanted to let customers find and buy a container themselves, in minutes, without ever picking up the phone.
The challenge
An inventory that existed, but wasn't searchable
The equipment customers wanted was almost always in the network somewhere — the problem was that no single system knew where. Depot inventory lived in independent spreadsheets, condition reports arrived as scanned PDFs, pricing changed by hand in email threads, and container specs were scattered across hundreds of documents in inconsistent formats with no shared schema.
A customer looking for "a 40ft high cube, wind-and-watertight, near the Gulf Coast, under a specific budget" had no way to ask that question directly. Instead, every search became a manual relay through a sales rep who had to piece the answer together from memory and a handful of spreadsheets, which meant slow answers, inconsistent quotes, and lost sales to customers who simply gave up and went elsewhere.
The Solution
A natural-language marketplace built on top of a unified, always-current catalog
We built an extraction pipeline that continuously ingests listings, specs, condition reports, and pricing from hundreds of unstructured sources — depot spreadsheets, scanned PDFs, dealer emails, and inspection notes — and normalises them into a single structured, de-duplicated catalog that stays in near real-time sync with what is actually sitting at each depot.
On top of that catalog sits a natural-language search and purchase experience: customers log in, describe what they need in plain English — container type, condition, location, price range — and get matched results ranked by fit and proximity. From there, they can complete the purchase directly on the platform, with no sales call required unless they want one.
The Results
Self-serve search and purchase, at scale
The marketplace now indexes tens of thousands of container listings pulled from sources that were previously invisible to any single search, and the time from a customer's first search to a completed purchase has dropped sharply now that the answer is instant instead of routed through a rep.
Online conversion has climbed as customers get accurate, real-time answers on the first try, and sales teams have shifted from fielding routine availability questions to handling the larger, more complex accounts where a human conversation genuinely adds value.
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