Adani Ports and Special Economic Zone (APSEZ) is scaling its partnership with Kaleris to deploy AI-enabled container handling and optimisation tools across 15 terminals at nine domestic and international ports. The multi-year agreement supports APSEZ's $850 million outlay for decarbonisation and technology upgrades and its target of handling one billion tonnes of cargo annually. The rollout is projected to lift rubber-tyred gantry crane productivity by up to 20% and terminal truck productivity by up to 14%.
Scaling a unified digital backbone
The expansion builds on an initial Phase 1 deployment that covered six ports. Kaleris will now install its N4 Terminal Operating System and Advanced Optimization solution across the full 15-terminal network. The goal is a single digital backbone that improves yard utilisation, accelerates vessel turnaround, and delivers more predictable cargo movement for customers.
Kaleris's Advanced Optimization module targets specific yard operations. The expected gains-up to 20% crane productivity and 14% truck productivity-come from better planning, reduced idle time, and automated decision-making at the terminal level.
Executive perspectives
Ashwani Gupta, CEO of APSEZ, said AI-enabled automation is "the next frontier of competitiveness in ports and logistics." He added that the Kaleris integration will build on the company's existing end-to-end digital platform to improve productivity, turnaround times, and the customer experience.
Kirk Knauff, President and CEO of Kaleris, pointed to "tangible results already achieved through the partnership" and said the company's measurement of success-centred on customer outcomes-will now be amplified across APSEZ's full terminal network as it advances toward long-term capacity and sustainability targets.
Why this matters for operations
The productivity numbers give operations managers concrete benchmarks for what AI-driven yard optimisation can deliver. A 20% jump in crane productivity and a 14% improvement in truck moves translate directly into lower dwell times, faster turnaround, and less congestion-metrics that sit at the centre of terminal performance dashboards. The deal also shows how terminal operating systems are evolving from record-keeping tools into active orchestration engines. For operations managers looking to build expertise in AI-driven process optimisation, an AI Learning Path for Operations Managers offers structured guidance.
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