In cybersecurity, each era is defined by a shift in architecture. Firewalls dominated the 2000s. Endpoint protection and identity controls shaped the 2010s. Today, we are entering a new phase — one where cloud-native platforms, real-time data correlation, and AI-powered analytics are no longer optional but essential.

Nowhere is this transition more timely than in the Gulf Cooperation Council (GCC) region. As cloud adoption accelerates across the United Arab Emirates (UAE), Saudi Arabia, and neighboring states, national cybersecurity resilience has become a critical pillar of digital transformation. GCC organizations have a unique opportunity to leap ahead — bypassing legacy limitations and adopting next-generation security architectures purpose-built for today’s advanced threats.

The Core Shift: Security Is Now a Data Problem

For decades, cybersecurity focused on control: firewalls, proxies, endpoint agents, and network gateways. While these tools remain foundational, today’s adversaries have evolved. Attackers exploit gaps between systems, bypass controls through misconfigurations, and evade siloed defenses with increasing sophistication.

The result is a fundamental architectural shift: modern security is no longer solely about enforcing control — it’s about processing data. Effective defense requires ingesting, normalizing, and correlating telemetry across every layer of the enterprise: endpoints, cloud workloads, SaaS platforms, identity systems, and external intelligence feeds. When combined with AI-powered analytics, this data-driven approach transforms raw telemetry into actionable insights, allowing defenders to outpace attackers, rather than merely react, once an attack has been detected.

Cloud-Native Design: The Architecture That Scales

Traditional security information and event management (SIEM) systems and on-premises platforms struggle to meet the scale, flexibility, and speed required in modern hybrid environments. Cloud-native architectures, by contrast, offer elastic scalability that aligns directly with national digital transformation priorities across the GCC.

However, the scale of telemetry introduces new challenges. Global cloud storage volumes are projected to reach 100 zettabytes by the end of 2025. Storing and processing such massive datasets can quickly become prohibitively expensive — unless managed with modern design principles.

The solution lies in the security data lake: a unified, long-term, cloud-native repository capable of retaining years of structured and unstructured security data. Unlike legacy systems limited to weeks or months of visibility, a security data lake enables continuous historical analysis for threat hunting, compliance, and investigations.

Crucially, modern architectures decouple storage and compute. Instead of permanently allocating compute resources (as most legacy platforms do), serverless designs apply compute power only when needed, dramatically reducing cost while enabling faster analysis.

For example, by leveraging serverless infrastructure on Amazon Web Services (AWS), Anomali enables compute bursts across thousands of nodes, delivering correlations and searches up to 1,000 times faster, at a fraction of the cost of traditional solutions. This approach is particularly aligned to national resilience goals, where speed and efficiency are essential.

Real-Time Correlation at Petabyte Scale

Today’s attackers automate their reconnaissance, probing continuously for vulnerabilities across every layer of the enterprise. To keep pace, organizations must reduce detection time and response costs, which demands real-time correlation across petabytes of data.

By integrating telemetry from multiple domains — including firewalls, endpoints, SaaS platforms, identity providers, and threat intelligence — organizations gain visibility into attacks that no single control would detect alone. For GCC enterprises expanding hybrid and multi-cloud infrastructures, the ability to correlate across these diverse sources in real time is mission-critical.

AI Delivers Context, Not Just Alerts

Artificial intelligence is now widely marketed in cybersecurity, but much of it offers opaque conclusions without transparency — effectively adding noise rather than clarity.

True AI-powered defense must provide explainability. Anomali applies chain-of-thought (CoT) AI reasoning, ensuring every detection includes the rationale, evidence, and audit trail behind each decision. This transparency builds analyst confidence and accelerates skill development, particularly valuable as GCC nations continue building local cybersecurity talent and operational maturity.

Intelligence Closes the Gaps Left by Controls

Even with modern defenses in place, critical gaps remain. Studies show that many endpoint detection and response (EDR) solutions still miss up to 30% of advanced threats, thanks to sophisticated evasion techniques, configuration gaps, or partial visibility. Firewalls suffer similar challenges: misconfigurations and limited context allow adversaries to slip past perimeter defenses.

This is where intelligence plays a decisive role. By unifying diverse telemetry and correlating billions of daily security events, modern security analytics platforms fill these blind spots, delivering full-spectrum detection across hybrid environments. For critical infrastructure, financial institutions, and government entities in the GCC, closing these gaps is no longer optional — it is a resilience imperative.

Agentless, Serverless, Effortless

Managing thousands of endpoint agents introduces complexity, operational risk, and resource overhead. Cloud-native platforms eliminate much of this friction by integrating directly with cloud platforms, SaaS services, and enterprise infrastructure via secure APIs, allowing telemetry ingestion without deploying additional agents.

For organizations balancing hybrid complexity with cloud-first strategies, agentless deployment models dramatically simplify operations — enabling faster rollout, lower risk, and greater agility.

Why the GCC Is Uniquely Positioned to Lead

The UAE, Saudi Arabia, and neighboring GCC nations are investing heavily in smart cities, digital economies, and next-generation public services. These national ambitions require security platforms that are scalable, adaptive, intelligent, and capable of evolving alongside rapid technological change.

Cloud-native, AI-powered, intelligence-driven security operations are no longer a distant vision but an operational necessity. By embracing these architectures, GCC enterprises and governments are positioned not only to meet today’s security demands, but to set a global standard for the future of cyber defense.

The time to shift from fragmented controls to unified intelligence is now. The future of security isn’t about deploying more tools — it’s about building smarter platforms.

And the GCC is ready.

Wei Huang is the Chief Technology Officer at Anomali, a global leader in intelligence-driven cybersecurity solutions.

Semantic representations of information are crucial for the functionality of large language models (LLMs), which is fuelling a heightened focus on semantics within data and analytics (D&A) and AI. 

Data silos become entrenched and limit an organization’s capacity to draw insights from its data. Without understanding the relationships within data, the individual pieces of information become less useful.

Semantic approaches facilitate a shared understanding of business terms and their interrelationships, which is vital for providing the necessary context for generative AI (GenAI). In a Gartner survey on the evolution of data management, 44% of the respondents from AI-ready organizations reported that semantic alignment is a key factor in assessing the AI readiness of their data.

D&A leaders can enhance and expand their semantic understanding by leveraging emerging technologies such as knowledge graphs and augmented data catalogs, thereby unlocking greater value from their information resources.

What is Data Semantics?

Data semantics refers to the meaning and interpretation of data within a business-specific context, as opposed to focusing on the physical representation of data through a data dictionary or a business glossary. It involves understanding what a data element represents, how it should be used, and its relationships with other data elements. Without this understanding, data is of limited use for AI use cases.

Semantic modeling is a practice of connecting technical metadata with business metadata.

A business glossary serves as the foundation for all things “semantic,” documenting the meanings of business-related terms. When the semantics and rules of a business glossary are well-understood, it leads to better data quality, easier integration and greater usefulness, supporting interactions with LLMs. The glossary also supports business goals like reducing costs and managing risks by making definitions clear, consistent and easy to trace back to their sources.

Top Recommendations for D&A leaders

• -Upskill your data engineers with semantic modeling techniques such as the use of knowledge graphs in building business ontologies.
• -Introduce DataOps practices to “deliver value from data” more easily, quickly and broadly. Take a people-, product- and governance-centric approach.
• -Invest in converged data management platforms. Establish a platform engineering team that produces platform services for platform tenants.

Key Benefits of Data Semantics

Leveraging and governing semantics effectively enables:

• –Improved Data Understanding: Both people and applications gain a unified view of data and its structure. For example, if several medical e-commerce sites use consistent relationships between terms, applications can extract and aggregate information across these sites to support user queries or serve as input for other applications.
• –Knowledge Reuse: Relationships uncovered by one group can be reused or built upon by others for new use cases, allowing previously identified connections to be embedded in future work.
• –Enhanced Accuracy with LLMs:  Incorporating knowledge graphs into the training and inference processes of LLMs serves as a factual base (i.e., data and metadata source) for mitigating errors and hallucinations.
• –Enhanced Interoperability and Innovation: By adopting semantic modeling, organizations open themselves to a wider range of use cases and enable more effective data interchange.

Link Data from Different Sources to Derive Data Relationships

Semantic reconciliation plays a crucial role in effectively linking data from different sources. It is also essential for inferring relationships between disparate datasets. Without a clear understanding of the relationships, correlations and distinctions among the meanings of data from different modalities such as text, videos, images and structured data, organizations cannot fully realize the potential of their data assets.

Modern semantic tools use algorithms to find connections in data. These tools recommend the best ways to clean, organize and analyze information. They also track where data comes from and how it is used for better governance.

With augmented data discovery, algorithms automatically detect correlations, segments, clusters, outliers and relationships, presenting the most statistically significant and relevant results. By using these semantic approaches, organizations can connect information from different sources, uncover relationships and gain valuable insights that drive better decisions.

In business ecosystems, the degree of openness is driven by members’ strategies, common goals and shared interests. For example, governments, nongovernmental organizations, charities and community groups can collaborate on health or public policy issues, or in open-source developer communities. This creates an opportunity for exploiting the knowledge of data and the meaning of data in terms of what can be applied to several digital business moments.

Lastly Think Data Semantics Before Introducing Large Language Models

Organizations are spearheading transformative initiatives to implement large language models in order to transform their operations. However, data and analytics leaders often rush to integrate LLM capabilities without first ensuring these tools are aligned with real business outcomes. To maximize value, it’s essential to connect LLMs with robust semantic frameworks.

Knowledge graphs are a powerful foundation for leveraging LLMs in business contexts. These machine-readable data structures capture semantic knowledge about both physical and digital entities. These worlds include entities and their relationships, which adhere to a network of nodes and links forming the graph data model.

LLMs can streamline the creation of ontologies, which define categories and relationships within data. By using “few-shot” learning prompts—providing just a handful of examples—users can guide LLMs to generate base ontologies in open formats that suit their needs. These initial frameworks can then be refined for greater detail as required.

Additionally, LLMs support ontology mapping by helping users align entities and relationships across different datasets or systems. With targeted prompts and sample mappings, organizations can extract relevant connections from their data and improve accuracy through iterative refinement.

By adopting large language models alongside semantic representations like knowledge graphs and ontologies, organizations position themselves for faster deployment of advanced analytics solutions that deliver meaningful business value.

Check out our previous post NMK Interactive 2025 Sets New Middle East AV Benchmark

A Unified Front Door for Enterprise AI

Enterprises today face fragmented systems, with employees managing dozens of siloed applications and disconnected AI solutions. As a result, workers often lack access to the right data at the right time. ServiceNow AI Experience addresses this challenge by bringing workflows, data, and AI models onto a single intuitive interface.

By combining context-aware functionality with multimodal inputs — including voice, text, image, and web — the new interface simplifies adoption and reduces employee learning curves. Furthermore, it ensures that AI becomes embedded across every workflow rather than being bolted onto existing systems.

Transforming How Work Gets Done

AI Experience introduces a role-aware, intelligent interface that supports instant access to AI-powered agents. These agents learn continuously, operate transparently, and provide full visibility for employees. Consequently, tasks can be resolved faster, decisions are made more effectively, and organizations experience measurable gains in productivity.

Amy Lokey, Executive Vice President and Chief Experience Officer at ServiceNow, explained:
“By creating a unified, contextual, and intuitive AI Experience for the enterprise, we’re putting AI into the flow of work. ServiceNow is empowering people to collaborate with AI agents seamlessly and without friction.”

Key Capabilities of ServiceNow AI Experience

ServiceNow highlighted four major innovations within the new platform:

• AI Voice Agents: Provide natural, hands-free support that can retrieve information, update records, and solve complex issues.
• AI Web Agents: Navigate third-party apps and websites, completing tasks without APIs or manual integrations.
• AI Data Explorer: Connects insights across internal and external data sources, helping users track trends and pinpoint causes directly within workflows.
• AI Lens: Turns any on-screen element into instant action, allowing users to automate tasks and accelerate decisions in real time.

AI Experience and Customer Relationship Management

The platform also reshapes Customer Relationship Management (CRM). Traditionally, CRM systems act as static records of customer interactions. In contrast, ServiceNow AI Experience transforms CRM into an AI-first system of action.

For service teams, automation accelerates ticket resolution and request fulfillment. Meanwhile, sales teams benefit from an AI-powered Configure, Price, Quote (CPQ) solution that streamlines proposals. Therefore, employees can focus on building relationships while AI handles repetitive and manual tasks.

This approach not only reduces costs but also improves customer satisfaction, as interactions become more proactive, personalized, and efficient.

AI Control Tower: Governance and Security

A critical element of the new release is the AI Control Tower, a central hub for governing and monitoring AI assets. It ensures organizations can deploy ServiceNow AI Experience confidently while maintaining transparency, compliance, and security. In addition, ServiceNow announced expanded model provider flexibility. Companies can now select from ServiceNow’s platform-native LLMs or third-party providers such as Azure OpenAI, Anthropic Claude, and Google Gemini.

By aligning the most suitable model to each workflow, enterprises gain flexibility without sacrificing security. This makes ServiceNow AI Experience not just powerful, but also enterprise-ready.

Driving Transformation in the AI Era

The introduction of ServiceNow AI Experience marks a fundamental shift in how people interact with technology. It places AI at the forefront of workflows, ensuring that human employees can focus on higher-value tasks while AI agents handle routine, repetitive work. Moreover, it creates a foundation for organizations to scale AI responsibly, with governance and transparency built in from the start.

Visitors attending GITEX Global 2025 can see AI Experience in action at ServiceNow’s stand in Hall 3. With its multimodal, intelligent design, the platform demonstrates how enterprise-ready AI can drive efficiency, resilience, and lasting customer loyalty.

Read our previous post on IBM nybl AI Solutions Transform Industrial Operations

A New Approach to Industrial AI

At the heart of the collaboration lies Nybl’s n.vision platform, now combined with IBM’s WatsonX AI and governance capabilities. Together with IBM Maximo, the platform equips enterprises with secure and intelligent asset management. As a result, companies can reduce costs, increase reliability, and improve safety outcomes while maintaining compliance with international standards.

IBM’s Watsonx.Governance provides transparency, lifecycle management, and regulatory alignment, ensuring that AI adoption remains both responsible and effective. Meanwhile, Nybl brings deep sector knowledge, making the solutions highly adaptable to the complex needs of industries such as energy, water, and utilities.

Visual Intelligence in Action

A key component of the new solution is IBM Maximo Visual Inspection (MVI). When combined with Nybl’s n.vision, the platform analyzes large volumes of imagery from drones and cameras. Consequently, organizations can detect faults earlier, predict equipment failures, and recommend prescriptive actions that minimize downtime.

By automating quality checks and defect detection, the approach not only enhances safety but also streamlines workflows. Furthermore, it ensures that industries can uphold high operational standards without overburdening their teams.

Empowering Smarter Decisions

The collaboration also introduces two powerful modules within the NYBL ecosystem. Director powers real-time analytics and decision-making, while Stage provides intuitive visualizations for rapid response. Together, these tools enable leaders to make smarter operational choices and drive efficiency at scale.

According to IBM, this partnership reflects its vision for the future of enterprise AI. “At IBM, we believe the future of industry is AI-powered,” said Zaidoun Arbad, VP – Ecosystem, IBM Middle East and Africa. “By combining Nybl’s domain-specific innovation with IBM’s enterprise capabilities, we are enabling clients to transform operations and make smarter decisions in real time.”

Building AI with Purpose

For NYBL, the collaboration amplifies its mission to build AI grounded in science and ethics. Noor Alnahhas, Founder and CEO of NYBL, explained: “Our mission is to solve critical challenges across energy, agriculture, healthcare, and beyond. This partnership with IBM significantly scales our ability to deliver measurable impact while exporting innovation from the Middle East to the world.”

By focusing on purposeful AI, the partnership ensures that industrial innovation is not just efficient but also sustainable. Moreover, it highlights the importance of ethical AI development, with Alnahhas serving as a member of Dubai’s AI and Ethics Advisory Board.

Strengthening Global Technology Leadership

The agreement also allows IBM to integrate nybl’s innovations into its global portfolio, while supporting nybl’s ambition to position Middle Eastern technology on the world stage. Consequently, this collaboration strengthens the region’s influence in shaping the future of industrial AI.

Together, the two companies are creating an ecosystem where advanced, purpose-built AI drives real-world improvements. Whether preventing equipment failure, optimizing workflows, or enhancing safety, the combined capabilities of IBM Nybl AI solutions deliver measurable business value.

Looking Ahead

As industries worldwide face rising demand, increasing complexity, and tighter sustainability targets, AI-driven solutions are becoming indispensable. With this collaboration, IBM and NYBL demonstrate how trusted platforms like watsonx and Maximo can be combined with local innovation to create powerful, globally scalable solutions.

The launch in Dubai also reflects a growing trend: Middle Eastern companies are no longer just adopters of global technologies but exporters of innovation that impacts industries worldwide. With IBM Nybl AI solutions, the future of industrial operations looks not only smarter but also more resilient and ethical.

Check out our previous post on Thriwe Aina Launches in UAE to Redefine Customer Loyalty

The UAE has become the launchpad for Thriwe Aina, a next-generation AI concierge designed to transform customer loyalty. Announced in Dubai, this launch marks a major step in Thriwe’s journey as it pivots from a service-driven provider to a technology-first innovator. With Aina, the company aims to deliver loyalty programs that go beyond transactions and create meaningful, intelligent lifestyle experiences.

Why the UAE Was Chosen

The UAE continues to stand out as one of the world’s fastest-growing centers for artificial intelligence. Recent studies predict the country will rank third globally, behind only China and the United States, in AI’s economic contribution. Therefore, it is no surprise that Thriwe selected the UAE as the first market to debut its new concierge. By launching Aina here, Thriwe reinforces the nation’s role as a global hub for innovation and digital transformation.

Dhruv Verma, CEO and Founder of Thriwe, emphasized the importance of the move:
“Exceptional experiences build lasting loyalty. With Thriwe Aina, we’re not just enhancing engagement but redefining how loyalty is delivered in the digital age.”

What Sets Thriwe Aina Apart

Unlike traditional loyalty programs that focus on points or discounts, Thriwe Aina leverages AI to deliver seamless and inclusive concierge services. Moreover, businesses can integrate the platform quickly with their existing systems, minimizing disruption. In addition, it reduces operational costs while creating smarter, data-driven recommendations that anticipate customer needs.

For customers, Aina provides instant assistance, personalized suggestions, and natural multilingual conversations. Consequently, interactions feel effortless, relevant, and human, no matter the market.

The Future of Loyalty is Intelligent

The launch also signals a broader shift across the loyalty landscape. Businesses now need platforms that combine efficiency with personalization. Furthermore, AI enables companies to reduce their reliance on manual systems while increasing the quality of customer engagement.

“Launching first in the UAE reflects our confidence in this market as a global innovation hub,” Verma said. “Thriwe Aina sets a new benchmark for how loyalty can be seamless, intelligent, and inclusive.”

Delivering Measurable Impact

For businesses, Thriwe Aina creates tangible results:

• -Faster adoption with minimal operational disruption.
• -Automated query handling that reduces costs.
• -Data-driven insights that improve customer retention.

For customers, the platform becomes a trusted digital companion:

• Providing 24/7 personalized support.
• Anticipating preferences through intelligent recommendations.
• Enabling inclusive access through multilingual features.

As a result, loyalty becomes less about transactions and more about building long-term relationships.

Looking Toward Global Expansion

The debut of Thriwe Aina in the UAE is just the beginning. Entering the final quarter of 2025, Thriwe plans to expand its AI-driven ecosystem through strategic partnerships, customized offerings, and continued investment in machine learning. Meanwhile, the company is positioning itself as a leader in hyper-personalized loyalty solutions.

The UAE’s environment — one that blends bold digital infrastructure with forward-looking regulation — provides the perfect foundation for this journey. Therefore, Aina’s launch in Dubai represents more than a local milestone. It positions Thriwe as a global innovator, ready to redefine loyalty for the next decade.

Read our previous post, Check Point Wiz Partnership Delivers Unified Cloud Security

Check Point Software Technologies and Wiz have taken their strategic partnership to the next level with the rollout of a fully integrated cloud security solution. The new platform unites Check Point’s prevention-first cloud network security with Wiz’s Cloud-Native Application Protection Platform (CNAPP). Building on their February 2025 announcement, the two companies are now making the solution globally available. It delivers real-time visibility, AI-powered prevention, and unified protection for enterprises facing today’s complex cloud threats.

Why This Partnership Matters for Enterprises

As enterprise networks grow more distributed, the attack surface expands. Consequently, security teams face rising pressure to protect constantly changing cloud environments. The integration between Check Point and Wiz directly addresses this challenge. By combining visibility, prevention, and risk-aware remediation, the platform helps organizations secure their operations without sacrificing agility.

Real-Time Visibility and Smarter Prevention

With this integration, customers can view CloudGuard gateway configurations directly inside the Wiz platform. This visibility enables faster risk assessment and more informed action. Moreover, by including third-party firewall policies in Wiz’s analysis, teams can now reduce false positives and respond more effectively.

Oron Noah, VP of Product Extensibility and Partnerships at Wiz, noted: “We are helping teams understand their exposure and take action faster. This level of insight accelerates secure decision-making across the enterprise.”

Key Benefits of the Integrated Solution

The joint Check Point–Wiz offering provides several advantages for customers:

• Shift to prevention-first security – threats are blocked before they cause damage.
• Enhanced visibility and faster response – teams save both time and resources.
• AI-powered defense against zero-day attacks – protecting against the unknown.
• Reduced configuration risks – issues at the gateway level are identified and resolved quickly.

Furthermore, Wiz now integrates with Check Point Infinity Threat Exposure Management (CTEM). This allows companies to automate remediation flows, turning Wiz alerts into actions at the CloudGuard gateway. As a result, exposure times are reduced from hours to minutes.

Independent Validation and Market Impact

Check Point continues to demonstrate strong performance across network and cloud environments. In testing by CyberRatings.org, Check Point achieved a perfect 100% block rate with zero false positives. Meanwhile, Miercom’s 2025 benchmark report confirmed the Infinity Platform reached a 99.9% block rate against Zero+1-day malware and 99.7% prevention against phishing attacks.

A Global Solution for a Changing Threat Landscape

The new integrated cloud security solution is available worldwide as of today. By combining prevention-first network protection with CNAPP capabilities, Check Point and Wiz are offering enterprises a smarter way to defend their data, reduce risk, and stay ahead of attackers.

Check out our previous on Shure’s Middle East Growth Strategy and Audio Innovation

Why CMF Watch 3 Pro stands out

First, it tracks your world with a new dual-band five-system GPS for faster lock-on and improved route accuracy compared to the Watch Pro 2. You’ll feel the upgrade on busy streets and open trails alike. Plus, 131 sports modes keep variety fresh, while a personalized running coach builds and adapts plans to your level. Then, a four-channel heart-rate sensor enhances accuracy across various skin tones and intensities, making the data more trustworthy. With Active Score (powered by MET data), you get a simple weekly snapshot that nudges you to keep moving.

Deeper insight, smarter recovery

After each session, AI-powered summaries break down training load, recovery time, and even 5K/10K predictions. Forgot to press start? No drama. The watch auto-detects seven core activities to capture effort anyway. Meanwhile, day-to-day wellness stays front and center: SpO₂, stress tracking, guided breathing, hydration nudges, inactivity reminders, sleep, and women’s health support round out a fuller picture of you.

Your on-wrist assistant

Because life doesn’t pause, Watch 3 Pro brings ChatGPT integration for quick answers, reminders, and ideas via natural-language voice prompts. You also get a voice recorder with auto-transcription for notes on the move and an Essential News digest tailored to your interests. And yes, Bluetooth calling, gesture shortcuts, and 140-character quick replies keep things effortless. An additional microphone improves call pickup, so conversations sound clearer.

Design that says “you”

Style still matters. The precision-milled metal body pairs with soft-touch silicone straps in Dark Grey, Light Grey, and Orange. A vibrant 1.43-inch AMOLED with ultra-thin bezels delivers an Always-On Display and a 10% higher screen-to-body ratio than Watch Pro 2. Moreover, 120+ watch faces—including video, photo, and AI-generated options via Watch Face Studio—let you switch moods in seconds. Add full-screen or mini widgets for fitness, weather, music, or reminders, and make it truly yours.

Built for real life

The watch is IP68-rated for dust and water resistance, so it handles sweat, rain, and everyday spills. Battery life shines too: expect up to 13 days with typical use, around 11 days with heavier tracking, and about 4.5 days with Always-On enabled. A full charge takes ~99 minutes. Meanwhile, improved motion monitoring and a 6-axis accelerometer (a 50% boost over Watch Pro 2) make indoor workouts feel just as precise as outdoor ones.

Nothing X: one app to rule them all

All CMF watches are transitioning to the Nothing X app, which adds a cleaner UI, steadier syncing, and smarter health tools. Even better, you can connect activity data to Strava, Apple Health, and Google Health Connect. Manage your watch and audio in one place and keep the routine simple.

Price and availability

CMF Watch 3 Pro arrives in the UAE and KSA at AED/SAR 369. You’ll find it at key retail partners across both markets, including leading e-commerce sites, electronics chains, and carrier stores. Open sales begin soon; final dates are TBC.

Bottom line

CMF Watch 3 Pro makes moving feel easy—and fun. You get AI coaching, accurate tracking, and playful personalization at a friendly price. Choose a color, set a goal, and let tiny wins add up. Then go again tomorrow.

Check out our previous post, Ai Everything MEA 2026 debuts in Cairo

Why Cairo, why now

Egypt’s AI agenda is moving at a pace. Therefore, a dedicated platform that unites policy, enterprise, and research arrives at the right moment. The country is embedding AI across strategic sectors—from outsourcing and shared services to semiconductors, cybersecurity, cloud, manufacturing, digital health, fintech, energy, education, and digital public services. Consequently, Cairo offers both market scale and coordination with national priorities.

What AI Everything MEA brings together

The program convenes AI enterprises, startups, researchers, and decision-makers from 60+ countries. Attendees will explore frontier use cases, responsible deployment, and practical roadmaps for adoption. Additionally, the agenda pairs a high-level summit with a two-day immersive exhibition. That mix enables leaders to set direction and, at the same time, see technology in action. Notably, global tech companies—such as Atos, Cyshield, HPE, and IBM—are expected to participate.

The government and ecosystem lens

“Artificial Intelligence is rapidly transforming the architecture of global competitiveness,” noted Dr. Amr Talaat, Egypt’s Minister of Communications and Information Technology. He emphasized Egypt’s intent to shape the shift, not merely react to it. Accordingly, Ai Everything MEA serves as a bridge between global expertise and national priorities, turning strategy into deployment. Likewise, Eng. Ahmed El Zaher, CEO of ITIDA, highlighted the summit’s role in attracting deep-tech investment, empowering startups, and nurturing co-creation. Together, these messages underscore a clear goal: build an inclusive, outcomes-driven AI economy.

Investment, talent, and scaling

Beyond policy, the event leans into capital and capability. Over 200 venture capitalists from the wider GITEX network—managing more than US$1 trillion in assets—are expected to explore deals across Egypt and the region. Meanwhile, one of the region’s largest youth-tech academies will launch at the event. As a result, fresh engineering talent can plug into pilot projects and real-world mentorship, channeling Egypt’s 750,000+ annual graduates toward AI careers. In turn, startups gain a pipeline of skilled contributors and early adopters.

Use cases that matter

Sectors on display track Egypt’s strengths and the region’s needs. For example, secure cloud and resilient digital public services support efficient governance. Similarly, AI in healthcare enables triage, imaging support, and hospital operations at scale. In fintech, intelligent risk and fraud tools help widen access while protecting consumers. Furthermore, smart industry and energy use cases drive productivity and efficiency. Because these applications align with national missions, pilots can advance faster and deliver a visible impact.

Dialogue on responsible AI

Momentum must pair with trust. Therefore, Ai Everything MEA dedicates stage time to governance, ethics, and safety. Panels will tackle privacy-by-design, bias mitigation, data stewardship, and accountability frameworks. Additionally, public–private working sessions will outline how to translate principles into tooling and procurement. With that approach, participants can accelerate adoption and maintain public confidence.

Voices from the organizer

“AI has leveled the digital playing field,” said Trixie LohMirmand, EVP of Dubai World Trade Centre, global organizer of GITEX. She underscored Egypt’s focus on using AI to uplift citizens and strengthen the economy. Accordingly, Ai Everything MEA aims to act as a force multiplier—amplifying local ambition with global resources and partnerships.

What attendees should expect next?

First, a curated summit program tailored to policymakers, CIOs, and founders. Second, a showcase floor that maps solutions to outcomes—cost savings, productivity, and service quality. Third, structured investor–startup matchmaking. Finally, capacity-building workshops that convert interest into skills. Altogether, the format turns conversations into tangible next steps.

Bottom line

The debut of AI Everything MEA marks a defining chapter for the Middle East and Africa. Cairo will host a global conversation—and, crucially, a practical marketplace—around responsible, scalable AI. With MCIT and ITIDA anchoring national priorities, and GITEX coordinating the international ecosystem, the region gains a platform built for delivery. As a result, governments, enterprises, and startups can move from pilots to production with speed, trust, and shared purpose.

Check out our previous post, Tally MSME Honours 2025 celebrates UAE excellence

1) Tie security to business and IT strategy

Start with intent. Map risks, processes, and outcomes. Then select a unified platform that brings video, access control, ALPR, comms, forensics, and analytics under one console. Centralized operations improve collaboration across security, compliance, and IT. Better yet, the data stream—facility usage, incident patterns, dwell times—feeds safety improvements and smart resourcing.

2) Demand technical compatibility (and avoid lock-in)

Architect for choice. Favor open systems that talk to Active Directory, identity platforms, and your cloud. Open APIs let you add third-party tools and industry-specific apps. As needs change, you can extend the stack instead of ripping it out.

3) Put cybersecurity and compliance at the core

Treat physical security like any business-critical workload. Encrypt data in transit and at rest. Enforce granular roles, MFA, and least privilege. Keep full audit trails. Then align with recognized frameworks and certifications such as NIST CSF, ISO/IEC 27001, and SOC 2. Ask vendors to share their vulnerability management and disclosure practices. Transparency builds trust.

4) Specify reliability and performance up front

Downtime breaks safety. Therefore, write high-availability, SLA targets, and disaster-recovery requirements into the contract. Test failover. Size the system for growth in cameras, doors, and analytics. If you plan to add sites next year, design for that today.

5) Model total cost—and prove ROI

Go beyond license price. Include implementation, maintenance, storage, and training. Then quantify value: faster investigations, fewer truck rolls, less shrink, and leaner staffing through automation. A choice-driven path—cloud where it fits, on-prem where it pays—usually wins on both cost and control.

6) Check vendor depth and support

You will live with this partner. Review references across industries, roadmap cadence, and security track record. Next, probe support: 24/7 assistance, customer portal, documented playbooks, and named contacts for critical incidents. Continuous software updates should ship on a predictable rhythm.

7) Plan rollout and adoption like a product

Technology only works when people use it. Build an implementation plan with phases, pilots, and success metrics. Train operators and IT admins with hands-on sessions. Share quick-reference guides. Capture feedback, tune policies, and celebrate early wins. Adoption drives outcomes.

8) Test, measure, and iterate

Run a risk assessment before full deployment. Pilot in a live but low-risk area. Validate performance, compatibility, and usability. Measure mean time to detect, mean time to respond, and investigation speed. Then adjust. Repeat after each site or feature wave.

What convergence looks like in practice

In a unified design, a single identity follows the user from badge to browser. Threat intel informs both firewall policy and door rules. Camera analytics trigger IT tickets and SOC alerts. Meanwhile, operators rely on one console that blends physical events and cyber signals. As a result, investigations compress from hours to minutes—and audits become easier.

How to get started this quarter

First, pick two sites for a pilot and define three business outcomes. Second, align cyber and physical runbooks so alerts flow to the same queue. Third, harden the basics: MFA, encryption, patching, and role hygiene. Finally, brief leaders on ROI and risk reduction, not just feature lists.

Bottom line

The perimeter now includes people, places, and packets. By unifying platforms, setting clear standards, and planning adoption, IT leaders turn IT physical security into a force multiplier. The payoff shows up fast: fewer blind spots, quicker response, and stronger compliance—across every site you protect.

Check out our previous post, RDI paradigm shifts: how governments can adapt

2025 Gartner® Magic Quadrant for Hybrid Mesh Firewalls

Why hybrid mesh firewall matters now

Enterprises operate data centers, multiple clouds, and thousands of edges. Consequently, the attack surface stretches far beyond a single perimeter. Siloed tools slow response, inflate cost, and create blind spots. A hybrid mesh firewall flips that script. It brings a common policy model, shared intelligence, and coordinated enforcement to every access point. As a result, security leaders close gaps faster and prove outcomes with consistent telemetry.

What Check Point brings to the table

AI-powered threat prevention. Check Point uses its global intelligence (Infinity ThreatCloud AI) to feed real-time protections into gateways and cloud controls. Therefore, malware, phishing infrastructure, and evasive payloads meet updated defenses at every hop. The company positions this as a 99.9% block-rate approach against active attacks, which gives teams confidence during spikes.

Unified management. Teams orchestrate policy centrally across data center gateways, public clouds, and SASE edges. In practice, that means one rule base, shared identity context, and common logging. Moreover, AIOps insights highlight misconfigurations, capacity pressure, and policy drift—so engineers fix issues before they hit users.

Open platform. The portfolio exposes hundreds of integrations. Consequently, security ops can plug SIEM, SOAR, ITSM, and third-party telemetry into a single workflow. Because the architecture remains modular, organizations build multi-vendor stacks without losing end-to-end visibility.

Executive comment

“We are honored to be acknowledged as a Leader in the Gartner® Magic Quadrant for Hybrid Mesh Firewalls,” said Nataly Kremer, Chief Product Officer at Check Point Software. “Our open platform approach delivers industry-leading network security with the flexibility to integrate with third-party systems. As a longstanding cybersecurity leader, we remain committed to giving organizations the agility, optimal user experience, and cost efficiency they need to stay protected.”

Customer perspective, in the field

Operations teams want a single pane of glass for inside-the-network, perimeter, and cloud. One large U.S. sports organization described how it consolidates network, cloud, and email security under one console to avoid tool-switching during incidents. That consolidation frees engineers to handle game-day priorities instead of chasing alerts across systems. In short, unified control turns busy days into manageable ones.

Where the hybrid mesh firewall shows up

Core data centers. High-throughput gateways enforce segmentation and east-west controls near critical apps.
Public cloud. Cloud-native controls and managed gateways apply the same policies around virtual networks, containers, and serverless endpoints.
SASE/remote edges. Branch and user traffic enter the same prevention fabric, so identity, device posture, and threat signals follow people wherever they work.

Because the fabric acts as one system, the change in windows shrinks. New sites, new VPCs, and new apps inherit guardrails automatically.

Outcomes security leaders can measure

Faster time to policy. Centralized management eliminates duplicate rule edits across environments.
Fewer gaps. Shared context aligns IDS/IPS, URL filtering, DLP, and anti-malware across the stack.
Lower noise. AI-curated intelligence reduces false positives and highlights the few events that matter.
Better experience. Consistent enforcement reduces broken paths and support tickets, which improves user productivity.

What to watch next

First, expect deeper identity and device-posture signals in policy, especially for high-risk users and privileged sessions. Next, anticipate tighter SASE alignment with branch automation so new offices come online in minutes. Finally, look for richer AIOps health checks that predict capacity, spot brittle rules, and recommend fixes with one click. As vendors ship these features, hybrid programs move from pilot to standard.

Gartner and trademark notes

Gartner publishes the Magic Quadrant as an analytical snapshot. The research reflects Gartner’s opinions and does not endorse any vendor, product, or service. Readers should pair the quadrant with technical validation and their own requirements. GARTNER, MAGIC QUADRANT, and PEER INSIGHTS are registered trademarks of Gartner, Inc. and/or its affiliates. Use them with attribution and respect for the original context.

Bottom line

Check Point’s Leader placement signals maturity for hybrid mesh firewall strategies. Organizations can run AI-powered prevention at the core, in the cloud, and at the edge without juggling five consoles. With one policy model, one intelligence source, and one operational rhythm, teams get what they need most: fewer gaps, faster moves, and a safer network for the business.

Check out our previous Dubai AI Seal Tier S: Yango earns top certification