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<a href="https://wearetechwomen.com/inspirational-woman-charlotte-webb-operations-and-marketing-director-hyve-managed-hosting/#">Originally published by We Are Tech Women</a>
With 15 years of marketing experience under her belt, Charlotte Webb is an accomplished marketing professional driven by a passion for creativity, innovation, and collaboration. Charlotte’s work in crafting effective marketing strategies and communication plans will continue to drive Hyve’s future goals of global expansion and success.
<h4>Tell us about yourself and your background.</h4>
Of course! I am <a href="https://www.linkedin.com/in/charlotte-webb-85569838/?originalSubdomain=uk">Charlotte Webb</a>, a Marketing and Operations Director at <a href="https://www.hyve.com/">Hyve Managed Hosting</a>. At Hyve, I lead our global marketing and operations initiatives. In my current role, I am also responsible for aligning our regional teams in the UK, US, and Germany with Hyve’s overall growth strategy.
I joined Hyve amid the pandemic to take the reins of the marketing team and oversee brand integrity, coordinate sales efforts, and lead the marketing team. With over 15 years in marketing, I have developed a strong grasp of key marketing tools, so when I joined Hyve, I used this expertise to enhance market awareness of our brand and offerings and to align our brand messaging closely with our reputation-building efforts. Changes in our marketing strategy led to the expansion of the marketing team and focus on lead generation to increase our sales pipeline and build brand equity. From the success and growth of the team and integrating with every element of the business to align the marketing strategy, I landed the role of Marketing &amp; Operations Director, now overseeing the marketing, commercial and business operations on a global scale.
In terms of my working style and ethic, I thrive on challenges. I am always looking for new business directions and excited about the next hurdle and celebration.
<h4>What inspired you to pursue a career in marketing, and how did you know it was the right path for you?</h4>
I am probably one of those rare people who work in the same field they studied at university – Management and Marketing. I enjoyed drama, art, and English at school and never considered myself a “numbers person”. So, I think my passion for creativity helped me discover and later develop a passion for marketing and to contradict this, I spend a lot of my week now looking at data to define the next business move.
After university, I managed to get a job as a marketing graduate in the paint industry company, and since those early days in marketing, I have never looked back.
<h4>Throughout your 15-year journey in marketing, what has been the most significant lesson you’ve learnt?</h4>
Perhaps the biggest takeaway from my years in the industry is the power of data. In today’s digital economy, analytics and data are fundamental to effective marketing and sales strategies. At Hyve, we continuously track and analyse customers’ behaviour trends, and engagement metrics and use these insights to adjust our campaigns. Data-driven decision-making helps strengthen our gut instinct for identifying new growth and development opportunities. This approach allows a robust and more aligned business strategy that results in achievable marketing goals rather than superficial metrics.
<h4>How do you balance creativity with the more strategic elements of your role as Marketing and Operations Director?</h4>
The tech world is ever-evolving; therefore, an important aspect is the need for flexibility and collaboration. Agility keeps us on our toes as projects and priorities change rapidly. This ability to stay nimble is essential for adapting to change and seizing new opportunities for current market demands. People in the tech industry are also very collaborative, and our open office environment, naturally encourages collaboration. We love brainstorming across teams and incorporating insights from all departments into our marketing and sales strategies.
<h4>Hyve Managed Hosting is known for its innovation. How do you keep the marketing strategy fresh and aligned with that ethos?</h4>
As I mentioned, I am a strong believer in the power of data in marketing – for me, “data is king”. Our team dedicates a lot of time and energy to analysing data and metrics. Staying on top of internal and market-wide trends helps us innovate and keep the leading position in a competitive market like cloud computing. Our data-driven approach helps us produce timely insights and thought leadership articles on industry trends, as well as white papers and explainer videos – the exact type of content our target audience is interested in.
The diversity and agility we foster in our teams are also important. Drawing on a range of perspectives brings fresh ideas, helps innovation and allows us to respond quickly to new opportunities – all while keeping the process fun and engaging!
<h4>What’s one piece of advice you would give to someone looking to follow in your footsteps?</h4>
Don’t be afraid of failure it’s important to take risks and learn from mistakes. Each setback can provide valuable insights that will inform your future decisions and help a business grow. Instead of fearing mistakes, view them as stepping stones to growth. This mindset encourages innovation, ultimately leading to more effective solutions and successes in the long run. I believe that success will come to those who are creative and analytical and use data to create the strategy for the brand.
<h4>Based on your experience, what’s the key to building and leading successful marketing teams?</h4>
For me, the synergy of the team, supported by data insights, is a recipe for success. A great way to maintain this synergy is by ensuring that each team member not only understands their responsibilities but also stays up-to-date with their colleagues’ tasks, ideas, and experiences. This helps everyone see how each data-driven task contributes to our broader marketing and business goals.
I continuously ensure alignment with the company’s strategic goals and objectives within my team. I believe that in marketing, each element—social media, PR, or SEO—plays an important role in the company’s overall success, ultimately maximising its potential. Data, collaboration, and creativity are the core elements of effective marketing.
<h4>As someone who has worked with several big names like Allianz and AJW Group, how have those experiences shaped your approach to your role at Hyve?</h4>
The corporate world has taught me many lessons, including the importance of structured processes, collaboration and agility. These skills were very useful when I stepped into my new role as Operations Director at Hyve, focusing on refining the company’s internal processes and building collaboration between departments. For example, I saw great potential in building a stronger, more cohesive relationship between our sales and marketing teams by ensuring they understood each other’s goals. This allowed both teams to work in sync to strengthen Hyve’s brand and increase business opportunities.
<h4>How do you stay motivated and inspired in an industry that’s constantly evolving?</h4>
My biggest motivation is staying ahead of the curve and having no day being the same! Luckily, tech industry change is constant and inevitable as technology is ever-evolving. I am always trying to stay on top of the current trends and news, be organised, ask lots of questions, and be ready to react quickly. My Outlook calendar and to-do list are my best friends, and they help me manage and coordinate evolving tasks to keep everything aligned and on track.
<h4>Looking forward, what excites you the most about the future of marketing and the direction Hyve is heading?</h4>
The future of marketing is exciting and full of potential. Right now, the hot topic is how AI is evolving to support personalised customer experiences and enhance marketing exercises. I believe that now is the time to get involved in all these new opportunities, to make a difference and be part of what could shape the future. Hyve is excited to lead the way in this ever-evolving tech landscape and will try to stay at the forefront of impactful trends. I am motivated to be part of this enthusiastic company and help Hyve embrace these trends and continue to innovate in ways that resonate with our customers and drive growth.

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As the marketing and operations director at Hyve Managed Hosting, Charlotte Webb plays a crucial role in shaping the company’s marketing strategy.

Inspirational Woman: Charlotte Webb | Operations and Marketing Director

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The data centre is the heart of IT infrastructure, whether it be private or public cloud, dedicated servers, bare-metal servers, or any other solution including an off-site element. 
As the central point for data storage and processing, data centres are critical for business applications and services. There are therefore a number of components and processes in place to protect the data centre, including physical and digital security measures, cooling systems and power supply, and physical protection against fire, extreme weather conditions, and natural disasters. 
<h2>What are the components of a data centre?</h2>
<h3>Servers</h3>
There are two main types of servers used within data centres &#8211; rack servers and blade servers. Rack servers are flat devices which are stacked in racks or shelves. Blade servers are vertical modular devices, which are housed in a chassis, and take up less space than rack servers. 
<h3>Storage systems</h3>
Storage systems are used to manage and archive data. There are two types of systems used within data centres &#8211; block storage and file storage devices. Block storage is a method of storing data within blocks, which can be distributed across multiple systems. Block storage devices can include hard drives, solid state drives (SSDs), and storage area networks (SANs). File storage devices use a hierarchical structure with folders and subfolders, and can include hard drives, cloud-based file storage, and network-attached storage (NAS). 
<h3>Networking infrastructure</h3>
Connectivity is key with rapid transfer of data between data centres, organisations and end users required. This is achieved through a high performing network. Within the data centre itself, the network is supported by cables, routers, and switches connecting all devices, and allowing for data transfer between locations.
<h3>Cooling systems</h3>
The large amount of servers and hardware in a data centre generates a significant amount of heat. Effective cooling is essential to avoid overheating, which can lead to performance issues and hardware failure. There are several methods used to cool data centres &#8211; traditional solutions include using air conditioning and chilled water systems, while emerging solutions use technologies such as liquid immersion cooling. For more information, read our insight ‘<a href="https://www.hyve.com/insights/how-are-data-centres-cooled/">How are data centres cooled</a>’.
<h3>Power supply</h3>
Data centres generally use multiple power sources, with mains power as the primary source, and one or more redundant systems to ensure continuous supply. This can include backup generators and uninterruptible power supplies (UPS). 
<h3>Security measures</h3>
To protect the data housed within the centre, data centres use physical security measures. This can include perimeter fencing, biometric access, intrusion detection systems, and security feeds. Digital security measures such as firewalls will also be employed for the servers within the centre. 
<h3>Physical protection measures</h3>
Depending on the location of the data centre, the physical protection measures will vary. For areas liable to flooding, measures such as elevated construction and advanced drainage systems can be used. For areas with high winds and seismic activity, buildings will be reinforced. Data centres are generally built to withstand damage from fire, including the usage of fire-resistant materials, and automated fire suppression systems. 
<h2>What are the types of data centre?</h2>
<h3>Enterprise data centres</h3>
Privately owned by businesses for on-premise infrastructure.
<h3>Multi-tenant data centres</h3>
Data centres run by providers, with resources rented out for customers’ infrastructure, for <a href="https://www.hyve.com/cloud-hosting/">cloud hosting</a>, <a href="https://www.hyve.com/dedicated-servers/">dedicated servers</a>, or <a href="https://www.hyve.com/colocation/">colocation services</a>.
<h3>Edge data centres</h3>
Smaller facilities close to end-users for low latency, often used in combination with internet of things (IOT) technology.
<h2>Data centre tiers and what they mean</h2>
In the mid 1990s, the Uptime Institute implemented a system of tiers to standardise data centre availability and overall performance. With rankings from 1-4, the tiers evaluate the data centre’s capabilities, based on redundancy levels, uptime guarantee, staff expertise, and maintenance protocols. 
At a basic overview, the tiers are: 
Tier 1 &#8211; Basic capacity: no redundancy 
Tier 2 &#8211; Redundant capacity components: partial N+1 redundancy
Tier 3 &#8211; Concurrently maintainable: full N+1 redundancy of all systems
Tier 4 &#8211; Fault tolerant: full 2N+1 redundancy of all systems
Most enterprises will require at least Tier 3 data centres to house their infrastructure, as this allows for maintenance without downtime, and provides sufficient redundancy in case of any faults. 
<h2>What questions should you ask your hosting provider about their data centres?</h2>
As data centres are the core of the majority of IT infrastructure, it is important to find out about your provider’s data centres. 
<h3>Locations</h3>
Global data centre facilities allow you to host your infrastructure in the location, or locations, best suited to your organisation and your end users. Spreading your infrastructure across geographically diverse data centres will support redundancy and disaster recovery. You may also require data centres in specific locations to comply with data sovereignty requirements &#8211; for example, EU companies must store and process their data in the EU, or within a jurisdiction with similar levels of protection. 
<h3>Data centre tiers</h3>
<h3>To best protect your infrastructure, you should be looking for Tier 3 data centres as a minimum, as this provides full redundancy. If you are looking to host mission-critical sites and applications, you can consider Tier 4 data centres, or backing up your platform across multiple Tier 3 data centres.</h3>
<h3>Security measures</h3>
You will need to confirm the security measures in place at your provider’s data centre to ensure the safety of your data. This should include a combination of the measures described above, with physical measures to protect the building, and digital measures to protect the servers. The level of security required will depend on the sensitivity of your data.
<h3>Physical protection measures</h3>
Depending on the location of your provider’s data centres, they may be liable to natural disasters and extreme weather. If this is the case, you should find out what measures are in place to protect the building and equipment.
<h2>Our data centres</h2>
As a global hosting provider, we deliver hosting services in more than 35 locations worldwide. Our strategic partnerships with leading data centre specialists, including Equinix and Telehouse, provides our customers with access to world-class technology, with enterprise-class security, connectivity and performance.
All of our data centres are Tier 3+, with a minimum of N+1 at some locations, through to N+N at others. Power is fed diversely from separate national grids with UPS and on-site generators available to take over where necessary, ensuring no drop in service.
Find out more on our <a href="https://www.hyve.com/data-centre-colocation/">Global Data Centres</a> page.

A data centre is the physical location housing computing resources to store, process and manage data. This includes servers, storage equipment, and networking hardware.

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<a href="https://www.techradar.com/pro/bridging-the-gap-between-cloud-readiness-and-ai-integration">Originally published by TechRadar</a>
<a class="hawk-link-parsed" href="https://www.techradar.com/pro/best-ai-video-editors-of-year" data-analytics-id="inline-link" data-before-rewrite-localise="https://www.techradar.com/pro/best-ai-video-editors-of-year" data-hl-processed="none" data-custom-tracking-id="2428657059907464034" data-hawk-tracked="hawklinks" data-google-interstitial="false" data-label="Artificial Intelligence">Artificial Intelligence</a> is introducing a new wave of technological capabilities, and therefore, businesses are increasingly looking for ways to integrate it into their products and day-to-day operations. As businesses race to unlock the potential of artificial intelligence, they increasingly recognize that <a class="hawk-link-parsed" href="https://www.techradar.com/best/best-cloud-computing-services" data-analytics-id="inline-link" data-before-rewrite-localise="https://www.techradar.com/best/best-cloud-computing-services" data-hl-processed="none" data-custom-tracking-id="9241672255965561276" data-hawk-tracked="hawklinks" data-google-interstitial="false" data-label="cloud">cloud</a> infrastructure is essential. It may come as a surprise, however, that although 67% of companies report having advanced cloud infrastructure, only 8% have fully integrated AI into their business processes (Infosys &amp; MIT, 2024). And this figure highlights a clear disconnect that, despite cloud maturity, businesses are lagging behind when it comes to <a class="hawk-link-parsed" href="https://www.techradar.com/best/ai-writer" data-analytics-id="inline-link" data-before-rewrite-localise="https://www.techradar.com/best/ai-writer" data-hl-processed="none" data-custom-tracking-id="1141206346298642909" data-hawk-tracked="hawklinks" data-google-interstitial="false" data-label="AI">AI</a> implementation.
This article will explore the reasons behind this lag and outline the key strategies for businesses to align their cloud infrastructure with the specific demands of AI to unlock its full potential.
<h2 id="why-is-there-a-disconnect-between-cloud-and-ai-readiness-3">Why is there a disconnect between cloud and AI readiness?</h2>
There are many factors to consider when implementing AI and the most important of which is cost. Currently, the biggest challenge in adopting AI is the significant upfront investment required to create an AI-ready environment. The hardware costs alone often don&#8217;t match the short lifecycles of the technology, as it evolves rapidly and organizations need to continually upgrade their systems to meet the demands. As a result, it can be difficult to justify the long-term ROI of AI.
Many organizations are rushing to integrate <a class="hawk-link-parsed" href="https://www.techradar.com/best/best-ai-tools" data-analytics-id="inline-link" data-before-rewrite-localise="https://www.techradar.com/best/best-ai-tools" data-hl-processed="none" data-custom-tracking-id="1014438523685889307" data-hawk-tracked="hawklinks" data-google-interstitial="false" data-label="AI tools">AI tools</a> into their operations without fully considering the infrastructure implications. Despite widespread recognition of AI&#8217;s potential, as evidenced by 98% of executives expecting increased AI spending on the cloud, businesses often neglect the specific technical requirements of AI.
To effectively support AI workloads, organizations must prioritize compatibility, scalability, <a class="hawk-link-parsed" href="https://www.techradar.com/news/best-internet-security-suites" data-analytics-id="inline-link" data-before-rewrite-localise="https://www.techradar.com/news/best-internet-security-suites" data-hl-processed="none" data-custom-tracking-id="1416816694547200851" data-hawk-tracked="hawklinks" data-google-interstitial="false" data-label="security">security</a>, and cost-effectiveness. However, performance remains a critical factor, and striking the right balance between Graphics Processing Units (GPU) requirements and costs is essential. AI&#8217;s demanding nature necessitates cloud environments capable of handling intensive <a class="hawk-link-parsed" href="https://www.techradar.com/best/best-data-migration-tools" data-analytics-id="inline-link" data-before-rewrite-localise="https://www.techradar.com/best/best-data-migration-tools" data-hl-processed="none" data-custom-tracking-id="6648391172719414796" data-hawk-tracked="hawklinks" data-google-interstitial="false" data-label="data">data</a> processing, low-latency response times, and specialized hardware like GPUs or custom accelerators.
Another factor influencing the disconnect is the IT industry’s ongoing skills gap, with 84% of UK businesses currently struggling to source the talent they need to address their IT challenges. Since there are a limited number of skilled professionals who can manage AI workloads, even businesses that have prepared their cloud infrastructure may lack the expertise needed to fully embrace AI’s capabilities.
<h2 id="key-considerations-for-ai-3">Key considerations for AI</h2>
1. AI workloads
The specific AI requirements of different companies can vary significantly. For example, a company developing an advanced image recognition system may have different infrastructure needs than one building a sophisticated <a class="hawk-link-parsed" href="https://www.techradar.com/pro/best-ai-chatbot-for-business" data-analytics-id="inline-link" data-before-rewrite-localise="https://www.techradar.com/pro/best-ai-chatbot-for-business" data-hl-processed="none" data-custom-tracking-id="4670957827800788490" data-hawk-tracked="hawklinks" data-google-interstitial="false" data-label="chatbot">chatbot</a>. To address these unique demands, bespoke cloud optimization strategies are essential for businesses to consider.
Each AI project has unique resources and high-performance computing requirements. For example, one of our <a class="hawk-link-parsed" href="https://www.techradar.com/best/the-best-customer-database-software-of-year" data-analytics-id="inline-link" data-before-rewrite-localise="https://www.techradar.com/best/the-best-customer-database-software-of-year" data-hl-processed="none" data-custom-tracking-id="1954176238199697964" data-hawk-tracked="hawklinks" data-google-interstitial="false" data-label="customers">customers</a> is developing an alternative to neuro-symbolic architecture, combining neural and symbolic learning, which acts similarly to the human brain. The company needed a hosting provider for training one of their products &#8211; the Expert Verbal Agent (EVA) model, an LLM designed for thoughtful queries and problem-solving. Unlike many AI models, which only run on GPUs as their computational model, EVA can use CPU, GPU, or both. Consequently, they required a CPU-powered server for software development and testing.
2. Scalability
Scalability is vital for AI, but it must be balanced with cost-effectiveness. An AI environment should be able to adapt to changing demands, providing additional processing power when needed but this can be expensive.
AI workloads can be unpredictable and fluctuate in size. It&#8217;s common for AI workloads to be needed only for short, intensive periods of time, for example to regenerate a model. This often means that the hardware involved sits idle for long periods of time and therefore does not generate a return on investment. This is an important consideration for companies looking to build AI-enabled platforms, who should consider leasing time on pre-built environments as an alternative to ensure the best and most resource-efficient outcome. While public cloud models offer flexibility, they tend to be more expensive for such projects, especially during peak usage periods. Organizations need to carefully consider their scalability demands and choose the infrastructure that is right for them.
3. Security
Security is critical in AI <a class="hawk-link-parsed" href="https://www.techradar.com/best/best-project-management-software" data-analytics-id="inline-link" data-before-rewrite-localise="https://www.techradar.com/best/best-project-management-software" data-hl-processed="none" data-custom-tracking-id="6060279827121031304" data-hawk-tracked="hawklinks" data-google-interstitial="false" data-label="projects">projects</a>, especially when outsourcing GPU or processing components. Sensitive data must be protected to safeguard customer privacy. While public cloud models can be convenient, they may not offer the same level of security as private or hybrid cloud solutions, where servers are dedicated solely to a business. Businesses should evaluate the sensitivity of their data and select a cloud environment that aligns with the security and control requirements of their AI workloads.
AI security in the cloud is a critical concern as organizations increasingly leverage the power of artificial intelligence (AI) to process and analyze vast amounts of data in cloud-based environments. The first key aspect of AI security in the cloud involves protecting the AI models and data. Encryption and access controls are vital to ensure that sensitive AI models and training data are safeguarded from unauthorized access or breaches. Additionally, regular audits and monitoring are essential to detect any unusual activities or vulnerabilities that could compromise AI systems in the cloud.
4. Performance
Certain AI tasks require specific hardware to run most effectively. In some scenarios, GPUs are essential, while some projects require specialized AI chips or TPUs (Tensor Processing Units). These chips are specifically designed to deliver the best performance when processing machine learning workloads. It is extremely important for companies to understand the specific technical needs of each project when choosing the perfect architecture for running an AI model, as there are many variations of hardware that can be used for these platforms.
Understanding the memory requirements of the AI model being trained is also extremely important. Some models will not fit on a basic graphics card, while others will require huge amounts of onboard RAM to be processed at all. <a class="hawk-link-parsed" href="https://www.techradar.com/uk/tag/nvidia" data-analytics-id="inline-link" data-auto-tag-linker="true" data-before-rewrite-localise="https://www.techradar.com/uk/tag/nvidia" data-hl-processed="none" data-custom-tracking-id="1270365850585358297" data-hawk-tracked="hawklinks" data-google-interstitial="false" data-label="NVIDIA">NVIDIA</a>&#8216;s latest cards, such as the H100 NVL, have a whopping 188GB of HBM3 memory, allowing very large models to be trained. Cloud providers often have access to advanced hardware and infrastructure that can significantly improve the performance of AI algorithms and reduce training time.
<h2 id="steps-to-bridge-the-disconnect-3">Steps to bridge the disconnect</h2>
To bridge the gap between cloud readiness and AI integration, businesses can start by understanding their key requirements and clarifying desired goals for the AI. This will allow the creation of a comprehensive brief which is an essential first step.
Next, evaluate existing cloud capabilities and identify key goals and requirements in order to identify any gaps in performance, scalability, or data handling – all necessary for the effective use of AI <a class="hawk-link-parsed" href="https://www.techradar.com/best/the-best-android-apps-of-2022" data-analytics-id="inline-link" data-before-rewrite-localise="https://www.techradar.com/best/the-best-android-apps-of-2022" data-hl-processed="none" data-custom-tracking-id="3188558035258078808" data-hawk-tracked="hawklinks" data-google-interstitial="false" data-label="applications">applications</a>. Furthermore, establishing data management, security, and compliance policies ensures that quality data is readily available for AI initiatives.
Companies should also consider which cloud infrastructure best suits the unique needs of each AI project. For example, if security and regulatory compliance are priorities, hybrid or private cloud models, with infrastructure dedicated to a business rather than shared across businesses, maybe a better fit than public cloud options.
Finally, incorporating regular performance evaluations and iterative infrastructure adjustments will help maintain alignment with evolving AI capabilities, ensuring a strong foundation that adapts as AI technology advances.
<h2 id="working-with-a-managed-service-provider-3">Working with a Managed Service Provider</h2>
These steps can seem overwhelming to tackle alone, which is why some businesses opt to work with a Managed Service Provider (MSP) on their AI integration. Currently, 65% of UK businesses work with MSPs as they offer a holistic approach to AI optimization by supporting infrastructure design, compliance, and ongoing optimization. MSPs also help companies with their security posture through continuous monitoring to protect cloud environments from threats and vulnerabilities.
Additionally, MSPs can help bridge the skills gap, which remains a common barrier to successful AI adoption. In fact, 46% of businesses use MSPs to address the ongoing skills shortage. MSPs can help businesses achieve their AI goals cost-effectively by providing the most efficient infrastructure and hardware backed by their expertise and service. Collaborating with cloud infrastructure management experts also reduces the risk of misconfigurations as well as unnecessary costs, ensuring that businesses have an optimized and secure foundation for AI.
<h2 id="cloud-readiness-and-ai-go-hand-in-hand-3">Cloud readiness and AI go hand-in-hand</h2>
As AI continues to transform our lives and modern businesses AI integration will be essential for companies aiming to stay competitive. By tailoring cloud infrastructure to AI-specific requirements and leveraging the expert knowledge of MSPs, organizations can overcome the most pressing hurdles (financial, technical, and talent-related), to make the most of AI&#8217;s potential. With a strategic approach and the right support, businesses can lay a solid foundation that can not only meet current demand but also adapt as AI technology evolves.

Artificial Intelligence is introducing a new wave of technological capabilities, and therefore, businesses are increasingly looking for ways to integrate it into their products and day-to-day operations.

Bridging the Gap Between Cloud Readiness and AI Integration

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Resources

What our customers say about us

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Discover Private Cloud

All the benefits of cloud technology, with the increased security and control of dedicated hardware.

Managed Private Cloud

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Discover Dedicated Servers

Keep your sensitive data locked down in one of our high-powered, ultra-secure dedicated servers.

Dedicated Servers

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Discover Enterprise Cloud

Virtualise workloads on our multi-tenant cloud platform for increased flexibility, scalability and cost efficiency.

Managed Enterprise Cloud

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Discover Colocation

Eliminate the expense of maintaining your own infrastructure, while retaining complete control of your servers.

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Why choose Hyve?

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We take pride on our customer reviews, find out what our customers say about us.

Trustpilot Reviews

Success Stories - Baxter & Bailey

Success Stories - Medichecks

Success Stories - PTA Events

Success Stories - Broadlight

Success Stories - Testimonial

Hyve Managed Hosting Customer Reviews - Trustpilot 2021 #1

Hyve Managed Hosting Customer Reviews - Trustpilot 2021 #2

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0800 612 2524

General enquiries

Raise a ticket via our <a style="color: #8ac53f;" href="https://www.myhyve.com/?flush=true">MyHyve portal. </a>

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Sales enquiries 

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Accounts enquiries 

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For all media enquiries please contact
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For further information please see Section 13- Complaints of our <a href="https://www.hyve.com/resources/terms-and-conditions/">Terms and Conditions</a>
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What you can expect

Hyve Managed Hosting, 
The Office, 
1 Market Square, 
Circus Street, 
Brighton 
BN2 9AS

United Kingdom Office

Hyve Managed Hosting Corp, 
301 Congress Avenue, 
Austin, 
Texas, 78701, 
United States of America

USA Office

Hyve Managed Hosting GmbH, 
Großbeerenstraße 2-10 
Haus 1 
12107 Berlin 
Germany

Germany Office

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Find the relevant contact information for Hyve Managed Hosting here, or call us today on 0800 612 2524.

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