RIYADH, Saudi Arabia — (ARAB NEWSWIRE) – VECOW Co., Ltd., a global provider of embedded and industrial computing solutions, is strengthening its focus on Saudi Arabia and the wider Middle East as demand grows for the computing infrastructure needed to move artificial intelligence from the cloud and data centers into factories, transportation networks, smart infrastructure and other real-world environments.
The company’s regional ambitions are being showcased at LEAP 2026 in Riyadh, where Larisa Tseng, Regional General Manager for MENA & Türkiye at VECOW, is participating in the panel discussion, “Digital Trust as National Security.”
Tseng joins H.E. Liisa-Ly Pakosta, Minister of Justice and Digital Affairs of the Republic of Estonia; Dr. Hassan Sawaf, CEO of aiXplain; Ahmad Halabi, Managing Director of Resecurity; and other technology and cybersecurity leaders to discuss how nations can build secure, trusted and interoperable digital systems.

For VECOW, the discussion reflects a broader industry shift as AI increasingly moves beyond software into physical environments. The company believes the computing infrastructure supporting AI will play a critical role in strengthening security, resilience, data sovereignty and digital trust.
“Digital trust cannot exist only in regulation. It has to exist in the architecture,” said Tseng. “As AI moves into transportation, manufacturing, robotics, smart cities and critical infrastructure, we need to think about the entire system—where data is processed, where decisions are made, how quickly systems respond, and whether they continue operating reliably when connectivity is limited.”
VECOW specializes in industrial computing, AI computing and edge systems that enable intelligent applications outside traditional data-center environments. Its technologies support manufacturing, transportation, defence and smart infrastructure, delivering the computing layer needed for AI applications in demanding real-world settings.
While cloud platforms remain essential for training AI models and processing large-scale data, VECOW sees growing demand for Edge AI, where computing happens closer to the source of data generation.
“If an intelligent system needs to respond in milliseconds, local processing may be necessary. Where information is particularly sensitive, organizations may want to limit the amount of raw data leaving a site, and in critical environments, systems may need to continue operating even when network connectivity is interrupted,” Tseng added.
VECOW believes that as AI becomes embedded in physical infrastructure, digital trust evolves into physical trust, making reliable and resilient computing platforms increasingly important.
Saudi Arabia represents a significant growth market as the Kingdom accelerates investments in AI, digital transformation, advanced industry and intelligent infrastructure. VECOW is seeking to collaborate with system integrators, AI developers, technology companies, industrial organizations, infrastructure developers, universities and government stakeholders across applications including smart infrastructure, intelligent transportation, robotics, computer vision, industrial automation and advanced manufacturing.
“Our ambition in Saudi Arabia and across the Middle East is not simply to supply technology,” Tseng said. “We want to work with local partners and become part of the ecosystem that takes AI from experimentation into real-world deployment.”
About VECOW
VECOW Co., Ltd. is a global provider of embedded and industrial computing solutions specializing in AI computing, edge systems and industrial automation. The company delivers computing platforms for manufacturing, transportation, defence, smart infrastructure and other industries, enabling intelligence closer to where data is generated and decisions are made.
Media contact
Shreya Verma
Arab communications bureau
+971 521133926
[email protected]
This press release is issued through Arab Newswire (www.arabnewswire.com) — a press release distribution service for the Arab World, Middle East and North Africa (MENA).


