logo
Logicalis becomes first Cisco XDR CPS Specialisation Partner to offer global Cisco MXDR

Logicalis becomes first Cisco XDR CPS Specialisation Partner to offer global Cisco MXDR

Yahoo22-05-2025
LONDON, May 22, 2025 /PRNewswire/ -- Logicalis, the leading global technology service provider, today announces it has achieved the Cisco Extended Detection Response (XDR) Cisco Powered Services (CPS) Solution Specialisation and becomes a Cisco XDR CPS Specialisation Partner.
Logicalis is the first Cisco XDR CPS Specialisation Partner to offer Cisco XDR as a global Managed Service (MXDR), cementing the company's status as a leading managed security services provider.
Through Logicalis's global network of Security Operations Centres (SOCs), the company's MXDR services enable organisations to proactively manage threats and strengthen their security posture 24/7/365.
Speaking about the specialisation, Bob Bailkoski, Global CEO of Logicalis, said, "As cyber threats grow more complex, Logicalis continually remains at the forefront of next-generation cyber defence, enabling customers to stay cyber aware, cyber secure, and resilient. This new Cisco XDR CPS specialisation demonstrates our commitment to offering customers a range of the most advanced solutions on the market and showcases our close relationship to developing industry leading managed services together with Cisco. An incredible achievement from our Logicalis Security teams."
As Andrew Sage, VP Global Partners at Cisco, explains, "As one of only six Global Gold Partners, Logicalis continues to innovate and deliver leading Secure Managed Services to clients. We are proud to work in partnership with Logicalis to bring the best of Cisco XDR technology combined with top-tier Security Operation Centre delivery across the globe. Together, Cisco and Logicalis provide our customers with the confidence that their data is secure."
Artur Martins, CISO Logicalis Portugal, adds, "Built around Cisco's XDR technology, our MXDR service is designed to simplify cybersecurity by integrating threat detection, investigation, and response into a unified, cloud-native platform. By focusing on real-time visibility, automated correlation, and rapid incident response, we help organisations enhance their cyber resilience. The Cisco CPS gives customers confidence they are receiving the best-in-class managed service utilising the advanced technology from Cisco XDR."
In addition to securing the Cisco XDR CPS Solution Specialisation, Logicalis has also achieved Global MXDR status for Microsoft, joining only a handful of service providers qualified to deliver Microsoft's most sophisticated managed detection and response services.
About Logicalis
We are Architects of Change™. We help organisations succeed in a digital-first world. At Logicalis, we harness our collective technology expertise to help our clients build a blueprint for success, so they can deliver sustainable outcomes that matter.
Our lifecycle services across cloud, connectivity, collaboration and security are designed to help optimise operations, reduce risk and empower employees.
As a global technology service provider, we deliver next-generation digital managed services, to provide our clients with real-time visibility and actionable insights across the performance of their digital ecosystem including availability, user experience, security, economic performance and sustainability.
Our 7000+ 'Architects of Change' are based in 30 territories around the globe, helping our 10,000+ clients across a range of industry sectors create sustainable outcomes through technology.
Logicalis has annualised revenues of $1.8 billion, from operations in Europe, North America, Latin America, Asia Pacific, and Africa.
It is a division of Datatec Limited, listed on the Johannesburg Stock Exchange, with revenues of over $5.5 billion.
View original content:https://www.prnewswire.com/news-releases/logicalis-becomes-first-cisco-xdr-cps-specialisation-partner-to-offer-global-cisco-mxdr-302462210.html
SOURCE Logicalis
Orange background

Try Our AI Features

Explore what Daily8 AI can do for you:

Comments

No comments yet...

Related Articles

Jim Cramer explains how Microsoft, Meta and Nvidia led the Mag 7 pack in the first half of 2025
Jim Cramer explains how Microsoft, Meta and Nvidia led the Mag 7 pack in the first half of 2025

CNBC

time39 minutes ago

  • CNBC

Jim Cramer explains how Microsoft, Meta and Nvidia led the Mag 7 pack in the first half of 2025

CNBC's Jim Cramer on Tuesday pointed out that three megacap tech names managed to exit the first half of the year at all-time highs: Microsoft, Nvidia and Meta. He reviewed each company and explained why he thinks they have outperformed their "Magnificent Seven" peers. "Not FANG. Not Magnificent Seven. Just M-N-Ms," Cramer said. "The sole survivors of a brutal quarter from what used to be the most captivating group in the market." These stocks hit some "pretty hideous darn levels" earlier in the quarter, Cramer said, so it's worthwhile to examine how and why they managed to triumph. Microsoft disappointed Wall Street in January when its Azure cloud business put up lighter growth than expected. But when Microsoft reported again at the end of April, the cloud segment beat expectations, putting up 33% growth. According to Cramer, this development was enough to send the stock to the new high list. Artificial intelligence powerhouse Nvidia had a rocky start to the year. Wall Street soured on the stock as they feared Chinese startup DeepSeek could pose a threat to the company's dominance in the AI sector. Nvidia then had an "anemic bounce" coinciding with its annual GTC conference in March where it unveiled new technology, Cramer said. The stock then declined in April when the U.S. government hampered sales of its products in China, he continued. However, Cramer said, Nvidia rallied hard over the next few months because of "semiconductor superiority and persistent demand from the hyperscalers." These same factors were what sent Nvidia's stock roaring last year, he added, suggesting that perhaps "there was nothing wrong with Nvidia the whole time." Nvidia's AI chips, he continued, "remain unrivaled." Meta's run is tougher to explain, Cramer said. He suggested that Meta's stock got caught up in the broader decline of a number of growth stocks towards the beginning of the year. But in April, Meta's quarterly earnings results blew past the estimates, Cramer said. He said it seems the company's advertising abilities are especially strong. "Microsoft, Nvidia, Meta," Cramer said. "M-N-Ms. Melt in your mouth, not your hands." Click here to download Jim Cramer's Guide to Investing at no cost to help you build long-term wealth and invest The CNBC Investing Club's Charitable Trust holds shares of Microsoft, Nvidia and Meta.

There's Explosive Drama Between OpenAI and Microsoft
There's Explosive Drama Between OpenAI and Microsoft

Yahoo

timean hour ago

  • Yahoo

There's Explosive Drama Between OpenAI and Microsoft

The partnership that ushered in our age of AI is showing some major cracks. As the Wall Street Journal reports, OpenAI wants its longtime patron Microsoft to loosen its control on its AI products, while also seeking Microsoft's approval to let it become a for-profit company, which OpenAI has been planning for a while now. But the negotiations have turned ugly. And OpenAI is so frustrated with its benefactor that behind the scenes, executives are considering the "nuclear option": going to court and accusing Microsoft of anticompetitive practices, according to the reporting. That could bring down a review by federal regulators and a public campaign railing against the tech monolith. An antitrust investigation is something that Microsoft has been paranoid about: as Reuters notes, it gave up a board observer seat at OpenAI last year to get US and UK antitrust regulators off its back. It's a stunning breakdown in a relationship that's proven to be one of the most lucrative in tech history, per the WSJ. OpenAI arguably wouldn't be where it is without Microsoft's initial $1 billion investment back in 2019. And Microsoft wouldn't be able to cash in on the AI race — nor enjoy its considerable head start — without the breakout success of ChatGPT, a name that has become synonymous with AI itself. Like certain sparring couples, the pair are still publicly insisting that they're getting along famously. "We have a long-term, productive partnership that has delivered amazing AI tools for everyone," spokespersons for the two companies said in a joint statement, per the WSJ. "Talks are ongoing and we are optimistic we will continue to build together for years to come." There's a lot on the line here. Microsoft benefits from having the rights and access to OpenAI's intellectual property, which it integrates into its own AI offerings like Copilot. OpenAI received heavy investment from the Redmond giant, which became the lifeblood of the company. Both are locked into a revenue-sharing agreement, though OpenAI has recently moved to decrease what it shares with its partner. One point of contention is OpenAI's $3 billion acquisition of the coding startup Windsurf, according to the WSJ's sources. OpenAI doesn't want Microsoft, which has its own AI coding tool called GitHub Copilot that competes with OpenAI, to have access to Windsurf's IP — which again, under their current agreement, Microsoft technically would have the rights to. Another is OpenAI's lengthy endeavor to become for-profit by converting into a public-benefit corporation. Microsoft isn't against the move, but it's reportedly asking for an even bigger stake in the would-be corporation that OpenAI won't even countenance. The pressure's on OpenAI to complete the restructuring, because if it doesn't by the end of the year, it could lose out on an astonishing $20 billion in funding, notes the WSJ. Shortly prior to the paper's reporting, The Information reported that OpenAI wants Microsoft to relinquish its rights to all of OpenAI's future profits in exchange for a 33 percent stake in the new company. Further down the line, the current partnership is supposed to end if OpenAI ever achieves artificial general intelligence, or AGI, meaning a powerful AI that rivals or exceeds human levels of intelligence. It's not clear if this is even possible, let alone if it could be achieved any time soon, but Microsoft is reportedly demanding it keep its access to OpenAI's products even after this milestone, in what OpenAI sees as breaking the terms of the agreement. Cracks have shown elsewhere before this latest escalation. On top of benefiting from its investment, OpenAI has historically depended on Microsoft to supply the vast computing power necessary to train and run its AI models. But OpenAI has started to court others to fill this role as part of its massive Stargate Project, including software giant Oracle, which has agreed to buy $40 billion of Nvidia AI chips to power OpenAI's new US data center. OpenAI has even clinched a deal with Google to gain access to its vast computing capacity, Reuters reported last week. We'll have to see how this shakes out — but we're not necessarily anticipating a chummy conclusion. More on OpenAI: Sam Altman Says "Significant Fraction" of Earth's Total Electricity Should Go to Running AI

2025 Halftime: AI's Four Forces - What Happened, What's Coming
2025 Halftime: AI's Four Forces - What Happened, What's Coming

Forbes

time3 hours ago

  • Forbes

2025 Halftime: AI's Four Forces - What Happened, What's Coming

Demis Hassabis, Co-Founder and CEO, Google DeepMind, speaks at a Google I/O event in Mountain View, ... More Calif., Tuesday, May 20, 2025. (AP Photo/Jeff Chiu) Monday, June 30th delivered a triple whammy of news that perfectly captures AI's current state. Meta unveiled its Superintelligence Labs after spending $14.3 billion to invest in Scale AI and poach talent from OpenAI, Anthropic, Google and others. Microsoft claimed its AI diagnoses patients 4x better than doctors. And the White House launched an AI youth education pledge, acknowledging AI literacy is as essential as reading. These weren't isolated events. Over the past six months we've seen some of the most dramatic AI disruptions since ChatGPT's debut in November 2022. If you zoom out, they're symptoms of four converging AI forces reshaping at unprecedented speed every aspect of society from people to businesses to governments: compute, data, algorithms, and robotics (often referred to as 'physical AI'). Compute costs have plummeted 25x, synthetic data is reducing AI training expenses, breakthroughs like DeepSeek along with model updates from OpenAI, Anthropic, xAI, and Google continue to push the limits of scaling laws, and humanoid robot pioneers such as Tesla (Optimus), Figure AI and Agility Robotics are preparing to commercialize physical AI-powered robots starting in late 2025. Progress in any one of these forces would be impressive on their own. When combined, these forces are amplifying each other to create unprecedented opportunities for prepared businesses and existential threats for the unprepared. As we cross 2025's midpoint, it's time to assess what just happened and brace for what's coming. AI Force #1 • Compute: The Paradox of Plenty Compute is the raw processing power driving AI - the brain power. The first half of 2025 revealed a paradox: while compute options multiplied, actual GPU availability remained critically constrained. NVIDIA's Blackwell Ultra announcement promised 50% better performance at 25x less power—if you could get them. With 36-52 week lead times and allocation politics determining who gets chips, the "democratization" remains theoretical. We're seeing the rise of accelerated computing as GPU performance is growing 2x per year While NVIDIA's Project DIGITS offers $3,000 desktop AI, the real action stayed in data centers where Microsoft Azure's 35% growth meant fierce competition for H100s and A100s. Google's TPU v7 claims 24x better economics, but its hard to access them outside Google Cloud. Intel's Gaudi 3 at $125,000 looks attractive until you realize the software ecosystem barely exists. The brutal truth: despite AMD's quantization efforts and edge computing promises, if you need serious training compute in H1 2025, you're either paying NVIDIA's prices, waiting in line, or making do with inferior alternatives. DeepSeek's $6 million miracle wasn't about abundant compute - it was about doing more with less because they had no choice. What's next: Blackwell production ramps from 200,000 to 2 million units by December, finally breaking the GPU stranglehold. Expect large training cost reductions and mid-market companies achieving GPT-4 capabilities for under $10,000/month. AI Force #2 • Data : The Insatiable Hunger Data is the oxygen of AI. Without quality data, even the most sophisticated algorithms suffocate, making the difference between AI that demos well and AI that delivers measurable business value. The first half of 2025 marked data's shift from volume obsession to quality management, especially as all publicly-available internet data has essentially already been ingested into LLMs, creating a scramble for new data sources. Synthetic data - AI-generated information that mimics real-world patterns without containing actual user data - is a key part of AI's growth story. The synthetic data market is expected to reach $3.7 billion by 2030, but most implementations remain basic data augmentation. Every player, both small and large, continue to search for more data. Just look at Meta's $14.3 billion Scale AI investment - part 'acqui-hire' for sure, but it was also for direct access to Scale's data labeling expertise and access to enterprise data partnerships. As IP rights are being debated, a major ruling came when Anthropic's copyright victory legitimized training on copyrighted material. The hunger for data is ravenous. Scale AI is a key player in the AI data industry, specializing in data annotation and model ... More evaluation services that are essential for developing and deploying advanced artificial intelligence applications. The last two data frontiers remain stubbornly out of reach. First-party enterprise data is locked behind corporate firewalls (containing decades of proprietary business intelligence), so every AI firm is now focused on how best to partner (and penetrate) the enterprise. The other source is real-world sensor data that's critical for physical AI. While Tesla's builds its humanoid robot fleet Optimus, it will benefit from the billions of miles of driving data that synthetic generation can't replicate. What's next: The majority of major companies will adopt synthetic data strategies by December. The first AI model trained entirely on synthetic data will outperform human-trained models, ending the "data is the new oil" era. But the real battle shifts to enterprise data - expect aggressive partnerships and "data-for-compute" deals. AI Force #3 • Algorithms : Surpassing Scaling Laws If compute is brain power and data is oxygen, then algorithms are the neural pathways - the connections and patterns that determine how efficiently the brain uses oxygen to produce intelligence. And we are on the road to superintelligence - just read the essays from OpenAI's Sam Altman or Anthropic's Dario Amodei. The first half of 2025 shattered every assumption about scaling laws and compute requirements. DeepSeek's R1 bombshell - reportedly achieving GPT-4 parity for $6 million versus $100+ million - wiped out $1 trillion dollars in market capitalization and sparked global panic back in January. However, by June the markets were back at new highs as the industry realized that this wasn't just cost reduction, it was algorithmic innovation as they used mixture-of-experts, aggressive sparsity, and clever routing. There have been 50 major model releases in just the first six months of 2025, with lots of different sizes, features, and use cases (see the table below). 50 major large language models have been released in the first six months of 2025 Open-weight models closed the gap with their closed-weight counterparts. In January 2024, the leading closed-weight model outperformed the top open-weight model by 8.04% on the Chatbot Arena Leaderboard, and by February 2025 this gap had narrowed to 1.70%. Claude 4 Opus hitting 72.5% on SWE-bench while coding autonomously for 7+ hours showed reasoning, not size, wins. Google's Gemini 2.5 Flash at 742 tokens/second redefined inference economics. By June, enterprise costs plummeted from $10,000 to sub-$1,000 monthly for equivalent performance. The truth that every LLM researcher knows is that most top models are now within the range of +/- 5% of each other, so we're waiting for the next step-function in innovation. Some of the focus is shifting from model training to system design - companies seeing 60% higher ROI focus on prompt engineering, RAG implementation, and workflow integration. While the "bigger is better" model was questioned in H125, what is becoming clear is that there will be many flavors for lots of different use cases. What's next: The "bigger is better" era ends. Agentic AI takes over - expect many companies to start having customer service handled by autonomous agents and perhaps whole departments being run entirely by AI. Salesforce already reports 30-50% of work done by AI. AI Force #4: Robotics : From Labs to Loading Docks Robotics and physical AI represent the final frontier in business transformation, with over 4 million industrial robots now operating globally and installations growing at 7% annually. Tesla aims to produce "several thousand" Optimus humanoid robots in 2025 for internal use, targeting sub-$30,000 pricing that could revolutionize labor economics. Figure AI's $39.5 billion valuation after raising $1.5 billion demonstrates investor confidence in embodied intelligence, while Agility Robotics' Digit achieved the first commercial humanoid deployment at GXO Logistics. Figure Unveils Next-Gen Conversational Humanoid Robot With 3x AI Computing for Fully Autonomous ... More Tasks The business case has shifted from future promise to present reality. Industrial automation delivers 12-24 month payback periods for large-scale deployments, with robots operating at $0.75/hour versus human labor costs. Manufacturing labor costs drop 20-30% with robotic automation while productivity increases 150% in equipment manufacturing. Agricultural drones, numbering 620,000 worldwide and growing 40% annually, exemplify how physical AI transforms traditional industries through precision and scale. Breakthrough capabilities in 2025 include 24+ hour autonomous operation with 99%+ reliability, multimodal perception combining vision and touch, and natural language control eliminating specialized programming. Yet adoption barriers remain: battery limitations, integration complexity with legacy systems, and a critical skills gap in robotics operation. The winners embrace Robotics-as-a-Service models to reduce capital requirements, invest in workforce training for human-robot collaboration, and pilot solutions in controlled environments before scaling. What's next: The first 10,000+ humanoid deployment hits warehouses. China deploys over a million service robots. We start to see the first "dark factories" operating 24/7 without humans. Robot-as-a-Service becomes a new growth market as companies offload capital expenditures. Business leaders must act on converging opportunities The four forces create immediate risks and opportunities for today's business leaders. First, reassess infrastructure investments given that algorithmic advances can deliver 95% cost savings—your planned GPU purchases may already be obsolete. Second, implement edge computing to reduce cloud dependencies by 60-90% while improving response times and data sovereignty. Third, embrace synthetic data to accelerate AI development while maintaining privacy compliance, joining the 60% of projects already benefiting from this approach. Medium-term strategies should focus on building AI implementation expertise rather than model development capabilities, as the 1.7% performance gap between open and proprietary models makes execution more important than selection. Develop hybrid human-robot workflows in operations, targeting the proven 2-year ROI rather than full automation fantasies. Create comprehensive data governance frameworks that treat information as a strategic asset, enabling the multimodal integration that drives next-generation business models. For long-term positioning, prepare for the algorithmic efficiency paradigm where smaller, optimized models outperform larger ones, making capital-intensive infrastructure strategies obsolete. Build partnerships that provide access to specialized capabilities rather than attempting to develop everything internally. Most critically, invest in workforce transformation. The organizations lacking sufficient AI talent will become exposed and lose out to those who develop these capabilities. The convergence of plummeting compute costs, synthetic data accessibility, algorithmic breakthroughs, and practical robotics has created a unique window for business transformation. Organizations that recognize these forces aren't developing independently but amplifying each other will capture disproportionate value. The question isn't whether to embrace AI-driven transformation, but whether you'll lead it or be disrupted by competitors who do. The tools are accessible, the economics are proven, and the early movers are already capturing market share. What remains is execution and the window for strategic advantage is narrowing rapidly.

DOWNLOAD THE APP

Get Started Now: Download the App

Ready to dive into a world of global content with local flavor? Download Daily8 app today from your preferred app store and start exploring.
app-storeplay-store