Work / Enterprise Rail Shipment Pilot

Enterprise Rail Shipment Pilot

Enterprise delivery

Class I freight rail — Shipment-management pilot

Three-month engagement to launch the client-facing pilot of a new shipment-management app for a major Class I freight rail operator. Delivered on time with zero critical defects.

3-month engagement to launch the client-facing pilot of a unified, AI-assisted shipment-management app for a major Class I freight rail operator's enterprise shippers. Delivered on time with zero critical defects at production launch.

This was a 3-month engagement where I led delivery for an enterprise client engagement. The main goal: launch a client-facing pilot of a new shipment-management app.

We delivered with zero critical issues at launch.

Situation

The client is a major Class I freight rail operator. Enterprise shippers — large merchandise operators and intermodal partners — were navigating a fragmented digital footprint, where a plant operator managing rail cars touched many internal apps just to do daily work. Customer rapport on the legacy tracking platform was already negative, and "knowing where stuff is" was rebuilt every day across spreadsheets and inbox threads.

Customers wanted a single, secure, AI-assisted app that consolidated freight tracking, support cases, proactive alerts, and railcar pipeline visibility.

What I led

Delivery of the client-facing pilot — a single mobile + web app organized around a chatbot, with key shipment, schedule, and operations flows on top of the client's data platform.

Design leadership in Phase II — led design with a small in-house team, recovering and rebuilding from inherited design assets while keeping the operator experience coherent

Engineering + design in parallel in Phase III — coordinated engineering, design, GenAI, SRE, and data engineering against a 2-week show-something cadence, with the client's technical lead and design director reviewing

Vendor coordination — kept multiple delivery partners aligned across the work streams converging on this app

Pilot scoping for enterprise shippers — multiple pilot customers on different operating models, with one customer's data-sharing constraints treated as a real boundary on information flow, not an afterthought

Outcomes

Launched the client-facing pilot on time with zero critical defects at production launch — the explicit headline metric

Consolidated shipment tracking, support cases, proactive alerts, and railcar pipeline visibility into one secure, compliant app for enterprise shippers

Set up the operating model — sprint goals, RAID + decision log discipline — so the program could continue past the pilot

Established the case for a Phase III engagement extension to continue iterating on the customer-facing surface

Why this engagement mattered

Enterprise pilots like this one fail more often from organizational drag than from technology. The challenge wasn't the GenAI chatbot — it was holding scope through stakeholder turnover, rebuilding design capacity mid-flight, and threading one pilot shipper's data-sharing constraints without breaking the other's use case. Zero critical defects at launch in that environment is a delivery outcome, not a luck outcome.