Oscar Pernía, co-founder and CTO of the company, has summarized the main ideas addressed at CTAC 2026 and TOC Europe regarding standardization, interoperability, and data usage in the port industry
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Oscar Pernia, co-founder and CTO of NextPort.AI, has synthesized the main conclusions from the panels held at the Container Terminal Automation Conference (CTAC), organized by Port Technology International (PTI) in Valencia, and at the Terminal Operations Conference (TOC Europe) in Hamburg. Representatives from CMA CGM, APM Terminals, ATAI, Navis-Kaleris, and EuroGate participated in both forums. The focus of both events was the same concept: the Data Backbone, the data backbone that the industry needs as an enabler of automation and artificial intelligence.
Pernia describes a recurring diagnosis in these meetings: data at container terminals remains fragmented across multiple systems — equipment handling events (CHE), work instructions, maintenance logs — each in its own database and with its own interpretation of the associated information. This fragmentation constitutes, according to the panelists, the main obstacle to deploying automation and artificial intelligence solutions that work effectively.
The author points out that data is a prerequisite for automation, from the necessary digital harmonization of processes and systems, but also one of its most transformative results: automation turns operations into a traceable and recorded backbone from which terminal operators can control, predict, and optimize their business processes.
Regarding the general state of the sector, Pernia observes that the conversation is progressing: there are more mature and productized process automation solutions, the automation of equipment is becoming more applicable with the emerging focus on autonomous trucks that are being productized, and advances are being recorded in equipment control systems and supporting IoT solutions. However, despite the progress of the Terminal Industry Committee 4.0 (TIC4.0), with new relevant publications and a general alignment around frameworks such as ISA-95, standardization and interoperability remain “in their infancy,” according to his words.
At the CTAC panel, which included Francisco Blanquer Jaraiz (CMA CGM), Mike Andrews (APM Terminals), Gangadhar Gude (ATAI) and Rene Alvarenga (Navis-Kaleris) — Leonard Heilig from EuroGate was ultimately unable to travel to Valencia — the discussion started with a reference to the OSI model, which allowed the internet to become the backbone of how we work and live, and to the ISA-95 model as a specific layer scheme for the industry, taking existing systems into account to avoid “reinventing the wheel.”
Mike Andrews presented APM Terminals’ strategy regarding its database and its focus on asset digitalization, which begins with the sensorization of handling equipment and enables its lean method with more accurate and complete data. Rene Alvarenga presented the vision of Navis-Kaleris, which sees data as the basis for helping operators optimize their operations, referring to the need to close the execution gap and the role of the TOS provider in supporting their clients with optimization capabilities. Gangadhar Gude emphasized not replacing what already works, but the opportunity to leverage emerging technology and distributed intelligence among devices, highlighting the need for data to stop being a “black box.” Francisco Blanquer Jaraiz presented CMA CGM’s strategy in Big Data and its vision of what the new generation terminal will look like in connection with other processes in the shipping line, and as a key member of TIC4.0, he pointed out the need to facilitate integration and “liberate” the data.
In general, the positions of operators and technology providers point to a collective call to keep working so that data in terminals becomes more connectable, accessible, and understandable, so that processes can be accurately represented, and optimization solutions can be deployed effectively.
At TOC Europe, the debate continued with the same theme. José María Real Valero (Chema) from NextPort.AI referred to the work published in an article from Port Technology International, a dissertation with a practical vocation on how to transform the fragmented data sources of a terminal into what they call Enriched Job Stepping. Real Valero pointed out the limitations stemming from fragmentation: control room users lack a precise understanding of details at the container movement level, so when they need to resolve an issue, they resort to a trial and error approach; worse still, no learning occurs in the system about what worked or didn’t. The proposal is to unlock a large amount of data to obtain the full history, identify gaps, and detect optimization opportunities. In the case of NextPort.AI, this translates into generating a digital twin of the operation at the terminal, extendable to other areas such as maintenance or asset management in general. Pernia points to a common disconnection: operations advance with the TOS and maintenance does so with the CMMS, without an aligned view of performance or how to “coexist,” for example in maintenance scheduling.
Leonard Heilig from EuroGate explained how the group has developed operateMybox, “a digital platform that transforms logistics processes through a modular approach,” which already has a solid database built on TIC4.0 and on which “a digital twin, simulation, predictive analytics or AI can be built.” Heilig described specific modules of operateMybox applied in terminals and detailed their intelligent planners, based on that same database and that leverage “advanced analytics and machine learning to extract information from operational data in real-time” and “incorporate the dynamics of the operation to cover what is happening in the terminal in reference to workload, waiting times, driving times or container flows.” He also showed how asset digitalization allows EuroGate not only to measure operational KPIs and waiting times but also to generate predictive models, “connecting multiple data records” to support operations and, based on “a complete view of the cycle process, build machine learning or artificial intelligence on top of it.”
Heilig and Real Valero closed the session with shared conclusions around the concept presented, the Data Backbone: the industry cannot expect intelligent automation, nor a practical and seamless integration of artificial intelligence, if it does not first achieve a harmonized integration of data. A good data backbone consolidates planned, executed, and feedback data from operations into a complete and harmonized operational view, providing the basis for unlocking the full potential of automation and artificial intelligence.
The ideas collected by Pernía position the Data Backbone as a basis for consolidating planned, executed, and operational feedback data into a complete and harmonized view of the process. This structure is presented as a requirement to make intelligent automation and practical integration of artificial intelligence viable in container terminals.
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