Railway Logistics Management Platform
Contributing to a railway logistics SaaS product serving the North American market, spanning sprint execution, documentation, and AI-assisted workflow optimization.
Overview
This is an ongoing railway logistics product built for a client based on the North American market. The platform handles end-to-end railway logistics logistics managament, billing, and more for clients across the region, and my role sits across business analysis, project management, and technical documentation acting as the connective bridge between the product, the engineering team, and the client.
The Context
The product was already in active development when I joined. The primary challenge here wasn't building from scratch, it was maintaining and improving the current velocity and clarity in an environment where requirements were constantly evolving alongside the client feedback. Getting structured and staying structured, iteration after iteration, was the core of the work.
What I Do
- Acted as the primary point of contact between the client and the internal delivery team for requirement-related queries.
- Gathered and documented functional requirements from stakeholder discussions and translated them into structured user stories with detailed acceptance criteria
- Managing sprint execution end-to-end, including backlog grooming, sprint board maintenance, task tracking, and ensuring timely delivery of sprint commitments.
- Maintained and organized product documentation (SRS, process flows, API docs), ensuring everything stayed current with what was actually built.
- Reviewed test cases to ensure coverage matched the agreed requirements before handoff to QA.
- Researched and evaluated AI tools and techniques to identify opportunities to automate repetitive tasks within the team.
- Conducted testing sessions alongside QA to validate feature behavior against defined requirements.
Tools & Technologies
Azure DevOps · Azure Wiki · GitHub · Excalidraw · Postman · GitHub Copilot · Microsoft Suite
Outcome
The primary focus has been on building a documentation foundation that the team can actually rely on, something this product lacked when it started scaling. The AI automations has already surfaced workflow improvements that have reduced manual effort in recurring tasks within the team.