Tech News
Exelixi AI announces AI Advisory Board
Exelixi AI is pleased to announce the establishment of its world-class Advisory Board with immediate effect. This AI advisory board unites world-renowned academic and industry leaders to provide strategic counsel our firm towards the development of responsible AI solutions and drive innovation in financial services and other verticals.

“Our Advisory Board represents the pinnacle of AI and financial leadership. Their collective knowledge will help shape the future of AI in enterprise, and ensure our technology is aligned with industry best practices, client needs, and evolving regulatory expectations.” said Suren Vedantham – Group CEO for Exelixi AI.
The Advisory Board will play a vital role in guiding Exelixi AI’s strategy as it pioneers in AI innovation across financial services and other key sectors. By drawing on their deep domain expertise, the board will support Exelixi AI in developing cutting-edge AI-driven solutions that unlock’s new revenue opportunities, enhance operational efficiencies, and create transformative business outcomes for clients.
Meet the AI Advisory Board
Dr. Edward Altman

Dr. Altman is the Max L. Heine Professor Emeritus of Finance at the Stern School of Business, New York University, and Director of the Credit and Fixed Income Research Program at the NYU Salomon Center. Dr. Altman has an international reputation as an expert on corporate bankruptcy and credit risk analysis. He was named Laureate 1984 by the Hautes Études Commerciales Foundation in Paris for his accumulated works on corporate distress prediction models and awarded the Graham & Dodd Scroll for 1985 by the Financial Analysts Federation for his work on Default Rates and High Yield Corporate Debt. Dr. Altman is the creator of the world-famous Altman Z-Score Model, perhaps the most popular analytic method for determining the probability of default of global corporations.
In 2005, Dr. Altman was named one of the “100 Most Influential People in Finance” by Treasury & Risk Management magazine and is frequently quoted in the popular press and on network TV.
Dr. Altman has been an advisor to many financial institutions including Merrill Lynch, Salomon Brothers, Citigroup, RiskMetrics Group, (MSCI, Inc.), Paulson & Co., and Franklin Templeton. Dr. Altman was a Founding Trustee of the Museum of American Finance and was Chairman of the Board of the Interschool’s orchestras of New York, and current advisor to Golub Capital, a prominent private debt lender.
Dr Walter Gontarek – Chair

Dr. Walter Gontarek serves as chairperson of the AI Advisory Board. Walt is the CEO/Chair of Channel Digital, the parent of a FCA regulated provider of non-dilutive capital to the innovation economy. He also serves as Chair of Wiserfunding, which provides automated data-driven underwriting, portfolio management and regulatory solutions for confident SMElending decisions. He is also on the Board of Apollo-backed Catalina Holdings UK regulated insurer. He is a visiting fellow at Cranfield University and an Honorary Professor for Fintech at the University of Aberdeen. He holds a doctorate from Cranfield University in Finance.
Gary Haase

Gary brings over two decades of leadership experience in financial services. He was most recently Chief Operations Officer of CNA, a $13B publicly traded U.S. insurer. Prior to that, he spent 13 years at Apollo- backed Catalina Holdings in a range of roles, including Group COO, where he oversaw 30 completed transactions.
A Fellow of the Casualty Actuarial Society since 2006, Gary brings deep expertise in data and analytics, M&A and integration, and operational transformation. He holds a bachelor’s degree from the University of Iowa and an MBA from NYU Stern, where he has also taught graduate-level courses in statistics and data analysis. He currently serves on the boardof Bermuda-based Fleming Insurance Companies and advises global insurance and technology firms on strategy, acquisition and execution.
Tech News
Intel Core Series 3 Extends AI-Ready Performance to Value and Edge Computing Segments
Intel has introduced its latest Intel Core Series 3 mobile processors, aimed at expanding advanced computing capabilities to value buyers, commercial users, and essential edge deployments.
The launch reflects a broader shift in the industry, where performance, efficiency, and AI readiness are no longer confined to premium systems but are increasingly expected across all tiers of computing.
Built on the architectural foundations of Intel’s newer Core platforms and leveraging advanced process technology, the Core Series 3 processors are designed to deliver a balanced combination of performance, battery efficiency, and scalability. The focus is on enabling reliable, everyday computing while supporting emerging workloads, including AI-driven applications.
Driving Value-Oriented Performance
Intel positions Core Series 3 as a significant upgrade path for users operating on older systems. Compared to five-year-old PCs, the new processors deliver up to 47% improvement in single-thread performance and up to 41% gains in multi-thread workloads. GPU-based AI performance also sees notable enhancements, enabling improved responsiveness in modern applications.
This performance uplift is complemented by a strong emphasis on efficiency, with reduced processor power consumption and optimisations aimed at extending battery life for mobile systems.
AI Capability Moves to the Mainstream
One of the key differentiators of the Core Series 3 platform is the introduction of hybrid AI-ready architecture within the value segment. With support for up to 40 platform TOPS, Intel is enabling a new class of systems capable of handling AI workloads at the device level.
The platform also integrates modern connectivity standards, including Thunderbolt 4, Wi-Fi 7, and Bluetooth 6, ensuring compatibility with next-generation peripherals and networks.
Expanding into Essential Edge Deployments
Beyond traditional laptops, Intel is positioning Core Series 3 as a scalable solution for edge computing environments. The processors are designed to support a wide range of applications, including robotics, smart buildings, retail systems, and industrial deployments.
By combining AI acceleration with energy efficiency, the platform aims to deliver the performance required for real-time processing while maintaining operational reliability in diverse environments.
Ecosystem and Availability
Intel expects broad adoption across the ecosystem, with more than 70 designs from OEM partners set to launch across multiple form factors. Consumer and commercial systems powered by Core Series 3 are rolling out through 2026, while edge-focused deployments are expected from Q2 onwards.
Tech News
62% OF SAUDI LEADERS ARE FAILING TO USE THEIR DATA EFFECTIVELY, NEW CLOUDERA REPORT FINDS

Cloudera, the only company bringing AI to data anywhere, today released its latest global survey, The Data Readiness Index: Understanding the Foundations for Successful AI, examining how prepared enterprises are to support AI at scale. Surveying more than 300 IT leaders in the EMEA region, including strong insights from Saudi Arabia, the report finds that while AI adoption is growing, most organizations still lack the data foundation needed for success.
The findings highlight a sharp contrast in how effectively organizations track their data. Nearly 9 in 10 EMEA IT leaders claim complete visibility into where all their data resides, compared to just 32% of respondents in Saudi Arabia. Furthermore, 62% of Saudi respondents cite data access restrictions as a major roadblock to effective data use.
This gap highlights an emerging ‘AI readiness illusion’: the belief that organizations are prepared to scale AI even as critical data challenges remain unresolved.
“Enterprises aren’t struggling to adopt AI, they’re struggling to operationalize it beyond experiments,” said Sergio Gago, Chief Technology Officer at Cloudera. “AI is only as effective as the data that fuels it. Without seamless access to all their data, organizations limit the accuracy, trust, and business value that AI can deliver. You can’t do AI without data.”
AI Adoption is High, but ROI Remains Elusive
While AI is now deeply embedded across the enterprise, achieving consistent returns on investment remains difficult due to a sharp geographical divide in implementation hurdles. Across EMEA, the struggle is largely centered on the inputs, with data quality issues (18%) and cost overruns (16%) cited as the primary causes of lackluster ROI. However, Saudi Arabia presents a different challenge focused on execution. In the Kingdom, weak integration into workflows is the overwhelming barrier at 29%, nearly doubling the concern over data quality, which sits at 15%.
These regional nuances are further tangled by significant infrastructure limitations. Around 65% of respondents in KSA report that performance constraints have hindered operational initiatives, highlighting the immense difficulty of scaling AI across fragmented environments.
Bridging The Data Gap
At the core of these challenges is a significant disconnect between data optimism and operational reality.
The report highlights that 95% of KSA respondents are highly confident in their data, but only 32% of that data is currently fully governed. While this outpaces the broader EMEA region, where only 26% of data is governed despite 91% confidence, it highlights a critical execution gap that organizations are now racing to fill.
The Kingdom is uniquely positioned to bridge this divide with 100% of Saudi respondents ready to adopt new governance frameworks, and 79% being extremely willing to transform their operations. This regional commitment suggests that Saudi Arabia’s proactive approach will likely outpace its peers in the race toward AI and digital maturity.
Strategic Alignment and the Accountability Gap
While leadership in both the EMEA and KSA regions understands the necessity of data infrastructure, the execution and accountability frameworks are worlds apart. More than 90% of EMEA respondents report a well-defined data strategy tied directly to business objectives, while only over half (53%) of Saudi Arabian respondents feel the same level of alignment.
Accountability and internal culture further widen this divide. In EMEA, 69% of leaders hold the CIO or CTO chiefly responsible for data readiness, whereas in Saudi Arabia, only 35% place ultimate responsibility on this role, indicating a more emerging ownership structure.
Beyond accountability and alignment, respondents in Saudi Arabia face a unique internal hurdle: 50% struggle with insufficient data literacy, while nearly a third (32%) cite a lack of executive sponsorship.
Data Readiness Will Define the Next Phase of Enterprise AI
As enterprise AI shifts from experimentation to execution, data readiness is emerging as the defining factor separating leaders from laggards.
Organizations able to fully access and govern all their data, wherever it resides, are far better equipped to deliver trusted, scalable AI. Notably, every respondent in the report indicated their organization is willing to adapt existing frameworks to support true data readiness.
As enterprises confront the limits of the AI readiness illusion, the path forward is clear: unlocking AI’s full value will require more than ambition; it will demand genuine data readiness. Those that close this gap will be best positioned to drive lasting impact and lead the next era of intelligent business.
Tech News
OPTRO LAUNCHES AI-POWERED GRC CAPABILITIES FOR THE MODERN ENTERPRISE WITH AI GOVERNANCE, CYBER RISK, AND CONTINUOUS CONTROL MONITORING

Optro, the leading AI-powered GRC platform empowering enterprises to transform risk into opportunity, has announced several product capabilities to boost the effectiveness of customers’ risk management programs and enable them to innovate with AI confidently and responsibly. These capabilities follow shortly after the company changed its name to reflect what its AI-powered GRC platform enables: a single, coherent view across infosec, compliance, risk, and audit.
“Cyber risk now moves at machine speed, and legacy GRC tools can no longer keep up,” said Happy Wang, Chief Product and Technology Officer at Optro. “By leveraging AI to predict cyber risk, surface real-time insights, and accelerate mitigation, we help organizations shift from reactive reporting to proactive risk defense—building a true system of action that is ready for the AI era.”
Optro’s latest Risk Intelligence report found that AI governance program maturity is advancing, but unevenly. AI adoption continues to outpace AI governance, with 85 percent of organizations reporting they have integrated AI into their core operations or deployed it across multiple functions, while only a quarter report comprehensive visibility into employee AI use. At the same time, only 34 percent of organizations report their AI governance program is strategic and continuously improving. As these challenges become increasingly prevalent across industries, Optro has released the following product capabilities to help customers turn clarity into action:
- Unified AI Governance: Serves as the essential orchestration layer for AI governance. By bridging the gap between policies & frameworks, your AI tech stack, and human oversight, this capability enables a unified, automated approach. We ensure that AI risks are visible, compliance is streamlined, and governance policies are enforceable across your entire organization.
- Cyber Risk: Vulnerability Risk Monitoring: Provides a clear narrative of how a specific vulnerability affects an organization’s security posture and bottom line. This AI-powered functionality enables customers to understand the true business impact of a vulnerability. Included with IT and Cyber Risk Management (formerly IT Risk Management), it’s a paradigm shift in how organizations defend their digital perimeter.
- Continuous Control Monitoring: With AI-driven recommendations for the controls best suited for automation, and a library of ready-to-use monitor templates, teams can bypass manual setup to start monitoring controls immediately. This capability helps customers reduce manual effort, improve consistency, and gain more timely visibility into control performance. By automating evidence collection and surfacing potential issues earlier, teams can address gaps more efficiently and move toward a more continuous approach to assurance.
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