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Microsoft demonstrates new tools at Big Data show

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To demonstrate the advancement in cloud technology, Microsoft showcased live demos on Emotion Detection, IoT Remote Monitoring solutions and Social Analytics at the Big Data Show, that commenced on the 29th March at the Dubai World Trade Center. Demonstrations highlighting customers leveraging Microsoft technologies were also presented.

Attendees at the Microsoft booth were able to experience the power of Microsoft Cloud technology through the emotion detection application, by uploading their photographs. The emotional API in this latest cloud tool uses photo images as an input and runs a set of operations using the Face API, generating results through analyzing facial expressions. The new cutting edge cloud based technology provides emotion recognition algorithms that enable users to build more personalized applications. Emotions API in the tool identify eight core emotions-anger, fear, contempt, neutral, happiness, sadness and surprise- based on facial expressions and allocate numerical values for them accordingly.

Microsoft’s Azure IoT Suite was developed to provide a complete end to end solution for its customers. The first pre-configured remote monitoring solution delivered on the Azure IoT Suite was also demonstrated at the Big Data Show, revealing the ease of monitoring telemetry from devices over time for receiving actionable results. The IoT hub in the Azure IoT Suite has the capability to process massive volumes of data, and the stream analytics service helps detect anomalies and aids in archiving data from various IoT devices. This enables users to customize solutions and get the best of both worlds.

The third demonstration at the event utilized the tremendous influx of data extracted from social media for listening and analyzing it for intelligent actions. Social Media Analytics solutions have the ability to listen to social networks in real time and create analysis and visualizations through Power BI. Unlike many other dashboard solutions, Power BI can render live dashboards with moving charts and continuously updated visualizations for monitoring real-time streams from supported data sources.
Sample dashboards displaying predictive maintenance and health monitoring scenarios were also shown at the Big Data Show, focusing on Microsoft customers ThyssenKrupp and Dartmouth-Hitchcock Healthcare Systems. ThyssenKrupp draws on the potential of IoT and connects its elevators to the cloud to gather data from its sensors and systems that aid in transforming data into valuable business intelligence. While Dartmouth-Hitchcock Healthcare Systems is using Microsoft’s Cortana Analytics Suite and Microsoft Dynamics to utilize predictive analysis for prevention, lower healthcare costs and better patient care. The audience were able to experience how Microsoft technologies can be used to garner insights for improving business intelligence.

Necip Ozyucel, Cloud & Enterprise Solutions Lead, from Microsoft Gulf said “Cloud technology is fast becoming ubiquitous and is permeating all aspects of our daily lives. Demonstrations at the Big Data event are meant to communicate the relevance of latest cloud tools and the possibility of computers performing human functions. Always a step ahead, Microsoft aims to revolutionize modern technology usage by building applications that can also be used as tools for insights and intelligent actions, thus enabling our users to achieve more.”

More than 1500 regional business leaders linked to different industries were present at the Big Data show, in order to gain access to leading technologies for improving big data analytics practices in their domains. The technology breakthroughs presented at the event served to validate the power of cloud based innovation and reflected accurately upon Microsoft’s aims for what the future of cloud services has in store.

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SunTec Strengthens E-Invoicing Readiness with Mashreq Ahead of UAE Mandate

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SunTec Business Solutions and Mashreq are said to extend their long-standing compliance partnership into electronic invoicing as the institution prepares for the UAE’s mandatory e-invoicing requirements. This collaboration is built on seven years of joint work on Value Added Tax (VAT) compliance and positions the bank to meet the Federal Tax Authority’s (FTA) e-invoicing deadlines.


The UAE’s e-invoicing mandate, established under Ministerial Decisions No. 243 and No. 244 of 2025, requires businesses to issue structured, machine-readable XML invoices transmitted in near real time to the FTA through an Accredited Service Provider (ASP). Large institutions with annual revenues equal to or exceeding AED 50 million must be live by January 1, 2027, with ASP appointment required no later than July 31, 2026. For UAE banks operating across thousands of daily B2B transactions spanning standard-rated fees, exempt interest, and out-of-scope for VAT, the compliance challenge is among the most technically complex in any sector.

“For seven years, SunTec has been the compliance backbone for leading UAE financial institutions navigating an evolving tax landscape.

“Our e-invoicing product extends that same architecture—over-the-top, non-disruptive, and built from the ground up for the specific complexities of banking. We are proud to partner with Mashreq as they take this next step in digital tax readiness.”

Nanda Kumar, Founder and CEO, SunTec Business Solutions

“E-invoicing represents an important step in the UAE’s broader digital transformation agenda. As a bank that has consistently invested in digital innovation, Mashreq is focused on ensuring early readiness while maintaining operational efficiency. Leveraging proven platforms and partnerships enables us to accelerate this transition while staying aligned with evolving regulatory expectations.”

Nassim Tanouti, Global Head of Taxation, Mashreq

As the UAE transitions to e-invoicing, banks will need to operate in a hybrid environment where customers at different stages of adoption must be supported—ranging from conventional invoicing processes to real-time exchanges through ASPs. This introduces new operational considerations, as institutions must ensure seamless interoperability across these models. At the same time, e-invoicing creates a network effect, connecting banks, businesses, and service providers in a standardized ecosystem. This positions banks to move beyond compliance, enabling them to embed value-added services such as financing, reconciliation, and cash flow insights directly into invoicing workflows.


SunTec Xelerate e-Invoicing is built to integrate with existing banking and enterprise systems, allowing institutions to participate in real-time invoice validation and transmission without disrupting their core infrastructure. As an approved ASP and a certified Peppol access point, SunTec enables compliant connectivity within the UAE’s decentralized continuous transaction control and exchange (DCTCE) model, supporting secure and standardized invoice flows across the ecosystem.

The company’s Dubai-registered entity, SunTec (Xelerate) Business Solutions DMCC, was approved by the UAE’s Ministry of Finance as an official e-invoicing ASP following completion of all technical and regulatory requirements, including Peppol Access Point certification. The company maintains regional headquarters at Jumeirah Lakes Towers, Dubai, with dedicated implementation and support teams serving UAE financial institutions.


Under the UAE’s phased implementation schedule, the pilot program opens on July 1, 2026, for a selected Taxpayer Working Group. Voluntary adoption is available to all businesses from the same date. Mandatory compliance for large taxpayers follows on January 1, 2027, with all remaining VAT-registered businesses required to comply by July 1, 2027. Non-compliance carries penalties of AED 5,000 per month, per-document fines, and daily charges for unreported system failures.

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Tech Features

FROM SMART GRIDS TO SMART CITIES: THE NEXT PHASE OF URBAN INNOVATION

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Dr Fadi Alhaddadin, Director of MSc Information Technology (Business), School of Mathematical and Computer Sciences, Heriot-Watt University Dubai

Urbanisation is accelerating at an unprecedented pace, placing immense pressure on cities to become more efficient, sustainable, and resilient. Today, urban areas account for most of the global energy consumption and greenhouse gas emissions, making them central to addressing climate and resource challenges. In response, cities around the world are transitioning from traditional infrastructure systems to advanced, technology-driven models. The evolution from smart grids to fully integrated smart cities marks a new phase of urban innovation.

At the core of this transformation lies the smart grid. Unlike standard energy systems, smart grids use digital communication technologies to enable real-time interaction between energy providers and consumers. This two-way communication allows for more efficient electricity distribution, improved demand management, and the seamless integration of renewable energy sources such as solar and wind. As a result, smart grids not only reduce energy waste but also enhance reliability and support decentralised energy systems. They form the foundational layer upon which broader smart city systems are built.

However, the true power of smart cities emerges from the convergence of multiple technologies. The Internet of Things (IoT), artificial intelligence (AI), and big data analytics work together to create highly interconnected urban environments. IoT devices ranging, from sensors and smart meters to connected infrastructure continuously collect data on various aspects of city life, including energy usage, traffic flow, air quality, and public services. This data is then analysed by AI systems, which generate insights and enable real-time decision-making.

Through AI-driven analytics, cities can predict energy demand, optimise transportation networks, and detect infrastructure issues before they escalate. For example, intelligent traffic management systems can reduce congestion and emissions by dynamically adjusting traffic signals based on real-time conditions. Similarly, predictive maintenance systems can identify potential failures in utilities or transportation networks, minimising disruptions and reducing operational costs.

One of the most significant benefits of smart city technologies is their contribution to sustainability. Energy-efficient buildings equipped with smart systems can automatically regulate lighting, heating, and cooling based on occupancy and environmental conditions. Smart transportation solutions, including connected public transit and electric mobility systems, help reduce carbon emissions and improve urban mobility. Furthermore, integrated resource management systems enable cities to optimise the use of energy, water, and other essential services, supporting a more sustainable urban ecosystem. A notable example in the Middle East is Masdar City, which has been designed as a sustainable urban development powered by renewable energy and smart technologies. The city integrates energy-efficient buildings, smart grids, and intelligent transportation systems, demonstrating how digital innovation can support low-carbon urban living.

The Middle East is increasingly positioning itself as a global leader in smart city development through ambitious national strategies and large-scale projects. In Dubai, smart city initiatives focus on digital governance, artificial intelligence, and integrated urban services to enhance efficiency and citizen experience. Similarly, Saudi Arabia’s NEOM project represents a transformative vision of a fully automated and sustainable urban environment powered by advanced technologies. These initiatives highlight the region’s commitment to leveraging innovation to address urban challenges and drive future economic growth.

Beyond environmental benefits, smart cities are designed to enhance the quality of life for their residents. Digital platforms enable more accessible and efficient public services, from healthcare to administrative processes. Smart health systems can improve patient care through remote monitoring and data-driven diagnostics, while intelligent safety systems enhance security through real-time surveillance and rapid emergency response. These advancements contribute to more convenient, inclusive, and liveable urban environments.

Resilience is another critical dimension of smart cities. As urban areas face increasing risks from climate change, natural disasters, and infrastructure strain, the ability to adapt and respond effectively becomes essential. Smart grids play a key role in enhancing energy resilience by supporting decentralised power generation and rapid recovery from outages. Meanwhile, data-driven systems allow city authorities to anticipate and prepare for potential disruptions, improving overall crisis management and response capabilities.

Despite their many advantages, the development of smart cities is not without challenges. The integration of interconnected systems raises concerns about cybersecurity and data privacy, as large volumes of sensitive information are collected and processed. Additionally, the high cost of implementing advanced infrastructure and the need for standardised systems can pose significant barriers. Addressing these issues requires strong governance, clear regulatory frameworks, and collaboration between governments, private sector stakeholders, and technology providers.

In conclusion, the transition from smart grids to smart cities represents a fundamental shift in how urban environments are designed and managed. By leveraging the combined capabilities of IoT, AI, and data-driven infrastructure, cities are becoming more efficient, sustainable, and resilient. This transformation is not only redefining urban systems but also shaping the future of how people live, work, and interact within cities. As this evolution continues, smart cities will play a crucial role in addressing global challenges and improving the overall quality of urban life.

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Tech Features

WHEN UNCERTAINTY TESTS THE REAL OPERATING VALUE OF AUTONOMOUS AI TEAMS

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By Alfred Manasseh, Co-Founder and COO of Shaffra

For much of the past two years, AI has been discussed mainly in terms of pilots, productivity, and experimentation. But in moments of uncertainty, the conversation changes. This is when AI needs to move beyond pilots and into execution. When pressure rises, what matters most is speed, consistency, and coordination. The real question is whether institutions have the operational capacity to respond clearly, maintain continuity, and support decision-making under pressure.

In the UAE, that question carries particular weight because resilience, proactiveness, and digital by design have already been established as national priorities. This is no longer a futuristic idea. It is already being implemented across institutions.

This is why the conversation is moving beyond AI as a surface-level capability and closer to the operating core of institutions. In 2024, UAE federal government entities processed 173.7 million digital transactions and delivered 1,419 digital services, with user satisfaction reaching 91%. Once millions of people are interacting with digital systems, resilience depends not only on keeping platforms online, but on making sure information flows remain clear, response times hold steady, and service quality stays consistent under pressure.

Filtering signal from noise

In high-pressure environments, the first challenge is information overload. Fake information, true information, public questions, updates, and warnings all arrive at once, and institutions have to respond without adding confusion. Human teams remain essential because judgment and accountability must stay with people. But people alone cannot process that volume of information at the speed now required.

This is where Autonomous AI Teams become operationally valuable. AI is effective at dealing with large amounts of data, identifying patterns, and helping institutions filter signal from noise. Used properly, that gives leadership a stronger basis for communicating clearly, responding faster, and addressing confusion before it spreads.

Why governed systems hold up

Good governance is what makes AI dependable in sensitive moments. It is not only about speed. It is about consistency in messaging, consistency in how citizens and residents are served, and making sure people are well-informed. In uncertain situations, the public does not only need information. It needs information that is clear, timely, and trusted. Governed AI helps institutions provide that support without losing control or passing ambiguous situations with false confidence.

This is particularly relevant as research has found that six in 10 UAE employees use AI in their daily jobs, while IBM reported that 65% of MENA CEOs are accelerating generative AI adoption, above the global average of 61%.

The UAE can lead this shift because it is building around digital capacity at every layer, from infrastructure to service delivery to workforce readiness. The Digital Economy Strategy aims to raise the digital economy’s contribution significantly by 2031, while broader trade guidance has also framed the ambition as growing from 12% of non-oil GDP to 20% by 2030.

Working model in practice

This is also where Shaffra offers a practical example of how the model is changing. Through its AI Workforce Platform, Shaffra’s Autonomous AI Teams are already saving more than two million manual work hours per month and reducing operational costs by up to 80%. These systems can monitor inbound activity, classify issues, support fraud reviews, prepare draft responses for approval, and help institutions listen at scale to recurring public concerns.

In Shaffra deployments more broadly, this model has also delivered significant time and cost efficiencies across enterprise operations.

That does not replace leadership or human judgment. AI and humans play different roles, and the real value comes when they work together. It gives institutions stronger operational support, with greater speed, consistency, and control when pressure is highest. In the years ahead, the strongest organisations will be the ones that move beyond AI as a productivity tool and build it as a governed resilience layer that stays reliable when uncertainty tests every process around them.

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