As Middle East organisations move AI beyond pilots, Everpure will showcase how a unified, trusted and governed data foundation can help enterprises scale AI while reducing complexity.
As enterprises across the Middle East accelerate artificial intelligence adoption, the quality, accessibility and governance of data are emerging as critical determinants of whether AI investments deliver measurable business value. At GITEX 2026, Everpure (NYSE: P) will make the case for a data-first enterprise architecture, positioning what it calls “data primacy” as a foundation for scaling AI securely and efficiently.
Exhibiting at Booth H17-D40, the company will demonstrate how organisations can make enterprise data more accessible, trusted and governed across fragmented IT environments. The proposition addresses a growing challenge: while businesses are investing in advanced AI models and computing infrastructure, the data feeding these systems often remains dispersed across applications and silos.
“Organisations need to be able to access and manage their data without complexity to turn AI ambitions into business results.”
— Omar Akar, VP – METCA, Everpure
According to an IDC Global AI Readiness Survey cited by Everpure, 94% of IT leaders identify data quality as a determining factor in AI success. Poor-quality, inconsistent or inaccessible information can undermine AI outputs, restrict deployment and weaken confidence in automated decisions.
Everpure’s data primacy approach places data, rather than individual applications, at the centre of enterprise IT strategy. A shared and governed data foundation can help organisations reduce silos, establish a consistent source of information and provide AI applications and autonomous agents with controlled access to relevant data.
The approach begins with discovering, classifying and contextualising enterprise information to identify bottlenecks that could prevent AI initiatives from moving into production. This also helps businesses understand what data they possess, where it resides and whether it is suitable for AI workloads.
“As organisations across the Middle East look to turn their AI ambitions into business results, they need to be able to access and manage their data without complexity,” said Omar Akar, VP – METCA, Everpure.
The company’s message reflects a broader shift in enterprise AI strategy: scaling AI is not simply a matter of deploying more powerful models, but of building a reliable data architecture that supports performance, security, governance and operational efficiency.
