Close

Cant find what your looking for?

Optimize processes with ETA 2.0

Measure, predict, and act proactively on vessel delays

More than 1/3 of all container vessels arrive late. Would you like to know ahead?

Reliable scheduling: Precise ETAs for your convenience

Improve operations with ETA 2.0

Would you like dynamic and predictive ETAs for real time shipment data of +4,500 container vessels? And could you benefit from precise, machine learning-based ETAs from 48 hours onwards? Then this is for you.

Get a quick demo

Ports & terminals

If you are a port authority or a terminal operator or working as a tugboat or pilot operator, this solution will be perfect for you.

The container vessel predictions will help you optimize your utilization of assets as you can predict the precise ETA of the expected container vessels due to the comprehensive machine learning based algorithms.

Container vessel owners

Container vessel owners and shipping companies will find great use of the precise ETA forecasts to benchmark and measure.

A reliable data source is the most important thing when you aim to optimize your performance and benchmark your operations against competitors.

Logistic companies

In order to be able to act proactively and reduce costs, all logistic companies need to be able to rely on supply chain events, such as vessel arrivals.

Knowing that more than 30% of all container vessels are more than 24 hours delayed, we feel certain that you’ll profit from being able to measure precise ETAs.

Introducing ETA 2.0

If you know the schedule for a vessel, ETA 2.0 will make you even wiser.

A three-day delay across the Pacific Ocean does not always mean a three-day delay to the port in question. Sometimes, time can be gained in ports and sometimes you can lose time.

ETAs based on actionable, real-time data

The solution collects schedules for container ships and makes estimations based on both historical and real-time data and machine learning. If a vessel is going to Singapore and is delayed, it can figure out that it might be on time for its planned arrival in Hamburg further on, because it estimates that it can catch up some of the lost time.

How it works

Collection of data from multiple sources like carrier schedules, port schedules, and live and historic AIS data.

Calculation of ​the scheduled ETAs, based on machine learning and fueled by AI.

Real-time container vessel schedules and forecasts. Get precise estimates for arrivals and departures. All in one place.

Act proactively

Knowing that more than a third of all container vessels are more than a day delayed, we operate with both

  • Estimated time of arrival
  • Calculated risk of delay

With the ETA 2.0, you will know if the expected vessel is delayed and for how long. This makes you able to optimize your business. Get notifications when your expected vessels are delayed and act proactively.

Get in touch for more information