Neurovia AI Demonstrates AI-Driven Visual-Data Compression at LEAP 2026
Emirati AI technology company Neurovia AI demonstrated its visual-data optimisation technology, NeuroStream, at LEAP 2026 in Riyadh, highlighting how organisations could reduce the storage, bandwidth, compute and energy demands associated with the growing volume of visual data generated by AI and connected infrastructure.
The LEAP 2026 demonstration marked NeuroStream’s first introduction to the Saudi market. Headquartered in Abu Dhabi, Neurovia AI identified Saudi Arabia as a key market as organisations across the Kingdom expanded AI infrastructure and deployed cameras and connected systems across smart cities, transport, airports, public safety and other large-scale environments.
Rather than adding infrastructure capacity to accommodate growing video volumes, NeuroStream was designed to reduce the amount of visual data that needed to be transported and stored while retaining information required by downstream analytics and machine-vision applications.
The technology could be deployed within customers’ existing infrastructure, including on-premise and air-gapped environments, allowing visual data to remain inside an organisation’s own environment.
Khalifa Mohammed Alshehhi, CEO of Neurovia AI, said the rapid expansion of AI, cameras and connected infrastructure across Saudi Arabia was creating a parallel challenge around the storage, bandwidth, compute and energy required to process increasing volumes of visual data.
“More video does not automatically mean more intelligence – it means greater storage requirements, more bandwidth, compute and power, unless the data itself is made lighter first,” he said. Alshehhi added that optimising infrastructure before expanding capacity could help Saudi Arabia and the wider region build AI infrastructure that was both capable and more sustainable over the long term.
At LEAP, Neurovia AI presented side-by-side comparisons of original video and NeuroStream-processed output, allowing visitors to assess the visual results. The company said it validated performance using each customer’s own data during proof-of-concept deployments.
The technology was targeted at organisations generating continuous visual data at scale, including government and public-safety agencies, airports and transport operators, critical infrastructure and energy companies, real estate organisations and manufacturers.
