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3PL Owner-operator network · 750+ owner-operators · 4,600+ chassis

How Gulf Winds eliminates 15,000 hours of manual order processing annually with Melrose

15,000 hours of manual work eliminated annually
7 FTEs of manual capacity redirected to higher-value work
10× faster spreadsheet-based order processing
20% reduction in demurrage costs year over year
Alysse Ligon
“What makes Melrose different is that they understand our business at an operational level. Their AI technology doesn’t just extract order data, it understands the context behind each field and why it matters for freight operations.”
Alysse Ligon Director of Innovation, Gulf Winds International

About

An owner-operator network spanning nine U.S. port and rail markets

Gulf Winds International is a transportation leader that moves import and export freight through drayage, transloading, and intermodal service. Its network spans nine strategic port and rail markets from Houston to Baltimore and includes 750+ owner-operators, 4,600+ owned and maintained chassis, and 1.3M square feet of portside warehouse space. Gulf Winds continuously automates and innovates through in-house custom solutions and strategic partnerships, including its proprietary TMS, which automates 80% of loads. Through these investments, the company enables customers to keep freight on schedule and stay informed about their shipments at every stage of the journey.

Challenge

Manual order processing stalled growing freight operations

As Gulf Winds entered a rapid growth cycle, its operations team was managing an increasing volume of complex shipments and associated documentation. Director of Innovation Alysse Ligon recognized that the team’s existing, largely manual processes couldn’t support that scale and were adding operational friction.

To keep orders moving, logistics coordinators (LCs) were sifting through multi-page PDFs and CSVs for container numbers, pickup dates, and pricing rates, then keying these data points into Gulf Winds’ proprietary TMS. Each customer had their own file layout, so LCs spent significant time searching for key data and ensuring each detail was captured in the right operational context. The team did have a document-processing tool, but its limited format recognition often pushed teams back into manual data transfer when file layouts changed.

“We would spend two hours combing through a single CSV file,” shares Rosie Hernandez, Application Development Analyst. Across dozens of customers, that time added up quickly, pulling LCs away from driver communication, proactive issue resolution, and hands-on customer support.

Even with LCs spending hours carefully reviewing, manual data entry still left room for missing or mistyped container numbers. Without real-time visibility into these errors, Alysse and Rosie faced a greater risk of delayed freight movement or containers being left off a pickup. These issues could result in avoidable demurrage and storage costs and strain customer relationships.

For customers requesting new rates, LCs relied on historical pricing records, along with their own knowledge of fuel costs, deal structures, and market conditions, to price those requests. But this process became increasingly difficult to standardize as volume grew, leaving Gulf Winds with less control over margins, response consistency, and rate competitiveness.

Onboarding new LCs would have relieved some of the existing workload, but it wouldn’t have addressed the manual work. Instead, Rosie and Alysse began evaluating technology that could streamline Gulf Winds’ freight operations. The ideal solution would combine deep drayage expertise with AI that could reliably automate complex order processing.

Of the several logistics software options they evaluated, the only one that met their needs was Melrose. Its AI-driven freight platform and deep understanding of drayage processes convinced Alysse and Rosie they’d found a solution that could power Gulf Winds’ growth.

Too much of our team’s capacity was tied up in manual processes that were limiting our ability to scale. If we wanted to continue growing without adding overhead, we needed a truly purpose-built AI solution. That solution was Melrose.

Solution

AI order automation that codifies institutional knowledge and amplifies team capacity

Melrose integrated directly with Gulf Winds’ proprietary TMS, enabling the team to introduce AI without replacing the system they already used. To ensure the platform fit with existing operations, Melrose worked closely with LCs to map their order-processing steps and test the automated workflows against real shipment documents and operational requirements.

At every step, Melrose responded quickly to questions and refined the platform’s configurations based on team feedback. That hands-on partnership enabled smooth company-wide adoption.

Today, LCs have made Melrose a core part of their day-to-day. As files come in, the platform’s automated order entry identifies key details like container numbers and appointment times. The Melrose team even built a custom parsing workflow to accurately extract data from CSVs with non-standard formats and feed it into the same automated stream.

Because the platform understands the drayage context behind each field, it adapts to evolving customer formats, flags ambiguous information for human review, and populates the TMS with precise delivery orders. As LCs review any unclear order details, Melrose learns from that feedback, building a more complete understanding of each customer’s documents, order patterns, and operational preferences. Over time, the platform becomes increasingly accurate and can handle more of the work independently, ultimately enabling Gulf Winds to run the workflow without manual intervention.

With orders entering the TMS near-instantly upon receipt, LCs begin tracking and moving shipments within hours. That shift enables them to handle rising order volumes without slowing operations and share status updates with customers sooner, strengthening relationships. They also have more capacity to coordinate with drivers and proactively resolve day-to-day operational needs, supporting continuous business growth.

This overall reliability has helped Gulf Winds reduce missed containers and improve delivery execution, lowering the risk of demurrage fees, storage costs, and other delay-related expenses.

Encouraged by the success of order automation, Alysse and Rosie expanded Melrose to pricing workflows. Melrose worked with the team to codify their knowledge of competitive pricing, customer context, and negotiation patterns, so the platform handles customer rate inquiries like a human professional. With these handled, the Gulf Winds team can focus on more complex pricing decisions and customer requests.

Throughout the partnership, Melrose has served as an extension of the Gulf Winds team, staying highly receptive to LCs’ evolving needs. That ongoing collaboration ensures the technology continues to support the way Gulf Winds moves freight and serves its customers.

With Melrose, we can be sure the technology will capture every container number regardless of the document length. That level of accuracy reduces the operational risks associated with manual data entry and helps us move faster.

Results

Melrose redirects 7 FTEs’ worth of capacity to higher-value initiatives

With Melrose, Gulf Winds transformed order entry from a labor-intensive process into a scalable operational capability. As a result, LCs now have the time to move freight faster, deliver hands-on customer service, and support increasing order volumes.

Building on this momentum, Alysse and Rosie continue to encode more of Gulf Winds’ operational knowledge into end-to-end workflows. Their goal is to leverage Melrose and automate every step their LCs currently execute by hand, such as responding to pricing requests and processing EDI information, to help the team move freight faster.

“The Melrose team makes our problems their problems. That convinced us early on that they’re the right partner to help us build a more scalable operation.”
Alysse Ligon Director of Innovation, Gulf Winds International

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