Custom Solutions, Built for Your Operations.
Every port, terminal, and inland operator works differently.
Custom Solutions, Built for Your Operations.
Every port, terminal, and inland operator works differently.
PortXchange can design custom digital solutions that fit into how you already work.
Custom digital solutions — including AI and machine learning-based programs — are designed around the real constraints, systems, and data maturity of each port or barge. The result is a tool that adapts to your way of operations, not the other way around.
Our team combines former port professionals, captains, developers, and data scientists. We understand maritime operations from the inside — which means we build solutions that fit into them, rather than disrupting them.
HOW WE WORK
We begin by examining the data you already have, the systems you already use, and the decisions you need to make more confidently. From there, we design and build a solution that addresses the specific operational problem at hand, integrates into your existing workflows, and delivers measurable results.
The goal is always the same: help you understand your data well enough to act on it — and improve through use.
Our process:
• Understand
We map your operational reality: your data sources, systems, workflows, and where the friction is costing you most.
• Design
We build a solution around your constraints — not a generic platform configured to approximate them.
• Deploy
Solutions are delivered via API or direct integration, designed to work within your existing tools and procedures with minimal disruption.
• Improve
As the solution is used, data quality improves, outputs sharpen, and operational decisions become more confident over time.
WHAT WE BUILD
Depending on your operational challenge, a custom PortXchange solution might:
- Identify inefficiencies in port call planning and surface decision-ready recommendations
- Quantify emissions across Scope 1, 2, and 3 with clarity on assumptions and data gaps
- Integrate vessel, terminal, and operational data into a single, actionable view
- Automate reporting workflows that currently rely on manual input or paper documentation
If your challenge is operational, sustainability-related, or sits at the intersection of both — we build for it.
CASE STUDY: ETAPREDICTOR
The Problem
A leading barge operator was managing a large, complex inland fleet with vessels moving continuously across an extensive waterway network. With thousands of barges in operation at any given time, accurately predicting when each vessel would arrive was nearly impossible using existing methods.
Static ETAs — generated at departure and rarely updated — were regularly off by days. The consequences cascaded across the operation: towboats idled waiting for barges that weren’t ready, workforces sat underutilised, cargo owners missed production windows, and last-minute tow rebuilds added cost and disruption. The operator knew the problem was costing them in productivity, customer satisfaction, and commercial opportunity.
The Solution
The operator came to PortXchange with a clear brief: improve utilisation rates and operational productivity, with a solution that was fully interoperable and integrable into established workflows.
PortXchange developed ETAPredictor — an AI-based predictive engine delivered via API that continuously recalculates vessel ETAs as conditions change. Rather than generating a single static estimate, ETAPredictor draws on vessel-level data including size, cargo, and historical performance, as well as broader network conditions, to produce dynamic, real-time arrival predictions that update automatically throughout each voyage.
The solution required no replacement of existing systems. It integrated directly into the operator’s planning and dispatch infrastructure, delivering automated ETA updates at scale from day one.
The Results
Within six months of deployment:
- ETA prediction error reduced by over 50%
- Approximately 10,000 automated ETA updates processed per day
- Idle time and last-minute tow rebuilds measurably reduced
- Asset utilisation improved across the fleet
- Customer satisfaction increased through reliable, dynamic delivery windows
The long-voyage ETA errors that had been accepted as normal — sometimes stretching to ±10 days — were eliminated. Planning became proactive rather than reactive, and the operational data generated through daily use continues to improve prediction accuracy over time.
LET’S TALK
Tell us about your operational challenge and we will tell you honestly whether we can help — and what that might look like in practice.