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Author: Steve Fenton

  • hosted·ai v2.0.1 – now it’s easy to optimize GPU pools

    hosted·ai v2.0.1 – now it’s easy to optimize GPU pools

    #BuildingInPublic – the platform story so far

    In August 2025 we released v2.0, which brought together a lot behind-the-scenes stability and security improvements that we introduced to the hosted·ai platform earlier this year.

    We consider that to be our first stable release, and we generally have a monthly release cycle – so from now on, we’ll talk each month about new features in the platform, and what’s coming next.

    New to hosted·ai? Learn more about our GPU cloud platform or get in touch for a demo.

    We’re excited to announce the availability of hosted·ai version 2.0.1, with some great new features that make GPUaaS easier, more flexible, AND more profitable. Let’s get into it!

    #BuildingInPublic – the platform story so far

    In August 2025 we released v2.0, which brought together many stability and security improvements introduced to the hosted·ai platform during the year. We consider that to be our first stable release, and we generally have a monthly release cycle – so from now on, we’ll talk each month about new features in the platform, and what’s coming next.

    New to hosted·ai? Learn more about our GPU cloud platform or get in touch for a demo.

    GPU security + performance optimization

    hosted·ai handles GPU very differently to other platforms. Our GPU control plane enables up to 100% GPU utilization by combining individual GPUs into pools, and allowing the resources of the entire pool to be shared with multiple tenants at once (that is the basis for hosted·ai’s dramatic improvement in GPU unit economics).

    The hosted·ai platform has an extremely efficient task scheduler that context-switches tasks in and out of physical GPUs in the pool – but, how is this scheduling controlled?

    Introducing… the new GPU optimization slider.

    When a GPU cloud provider creates a pool, they assign GPUs to that pool and choose the sharing ratio (i.e., how many tenants you can sell the pool’s resources to). For any setting above 1, the new optimization slider becomes available.

    Behind this simple slider is a world of GPU cloud flexibility. The slider enables providers to configure the shared GPU pool to suit different customer use cases:

    • Optimized for Security: temporal scheduling is used. The hosted·ai scheduler switches user tasks completely in and out of physical GPUs in the pool, zeroing the memory each time. At no point do any user tasks co-exist on the GPU. This is the most secure option, but comes with more performance overhead.
    • Optimized for Performance: spatial scheduling is used. The hosted·ai scheduler assigns user tasks simultaneously to make optimal use of the GPU resources available. There is no memory zeroing. This is the highest-performance option, but it doesn’t isolate user tasks – they are allocated to GPUs in parallel.
    • Balanced: temporal scheduling is used, but without fully enforced memory zeroing. This provides a blend of performance and security.

    Why is this important?

    Service providers need the flexibility to handle any mix of heterogeneous workloads. That’s just as true for GPUaaS as it is for traditional IaaS cloud and hosting.

    Your GPUaaS needs to cater to a range of price/performance targets for different AI model training, tuning and inference use cases, as well as customers in simulation, gaming, research and so on.

    The hosted·platform enables you to configure your infrastructure and services accordingly:

    • Creating pools of different GPU classes
    • Configuring the sharing, security and performance characteristics of each pool
    • Configuring pricing and other policies for each pool
    • Enabling customers to subscribe to any mix of pools for different workloads

    Self-service/end user enhancements

    Also in this release, some handy improvements for end users running their applications in your hosted·ai environments:

    Service exposure

    We’re made it easier to expose ports for end user applications and services through the hosted·ai admin panel (and coming soon, through the user panel).

    Now your customers can choose how they present their application services to the outside world, through configurable ports.

    More self-service GPU resource management

    We’ve added new management tools for your customers too. Each GPU resource pool they subscribe to can be managed through their user panel, with visibility of the status of each pod; the ability to start, stop and restart pods; and logs with information about the applications using their GPU.

    Why are these things important?

    These enhancements are part of our mission to make GPUaaS as fast, easy and frictionless as possible for your end users (also, nobody should be forced to use CLI to do deep K8s management when they just want to restart a service)

    Furiosa integration

    In July 2025 we announced our partnership with Furiosa, a semiconductor company specializing in next-generation AI accelerator architectures and hardware. We’ve been working bring Furiosa device support to hosted·ai and this is now available in v2.0.1.

    Now service providers can create regions with clusters based on Furiosa, as well as NVIDIA. Once a region has been set up for Furiosa cluster, it can be managed, priced and sold using the same tools hosted·ai makes available for NVIDIA – and in future, other accelerator devices.

    Why is this important?

    Furiosa’s Tensor Contraction Processor architecture is designed to maximize performance per dollar and per watt for generative AI workloads.  The hosted·ai platform is designed to be accelerator-agnostic to give service providers flexibility in the AI infrastructure they build and sell. It’s all about flexibility to meet different use cases at different price/performance points.

    More information:

    Coming next:

    In final testing now – subscribe for updates:

    • Full stack KVM – complete implementation, replacing Nexvisor
    • Scheduler credit system – expanding GPU optimization with a credit system to delivers consistent performance for inference in mixed-load environments
    • Billing enhancements – more additions to the hosted·ai billing and metering engine – more ways to monetize your service
    • Infiniband support

  • Neocloud Survival Guide

    Neocloud Survival Guide

    NEOCLOUD SURVIVAL GUIDE

    How to 5x your GPU revenue + margin

    Most Neoclouds have a big problem: it’s hard to see a future where the business is actually profitable.

    Some companies in this space have already folded. Many more are struggling to make the numbers add up, because super-high GPU capex + low utilization + price erosion + commoditization = little or no ROI.

    Let’s fix that.

    Everyone agrees that AI is the future, but how do you build an infrastructure business for AI that will still be in business next year, let alone in five years’ time?

    Get your copy of the Neocloud Survival Guide, and learn how to 5x your GPU revenue and margin.

    Contents

    The Neocloud profitability problem

    Rethink the madness: change 4 things

    Your new game plan

    5x ROI illustrated

    Next steps

  • One year of hosted·ai: AMA with James, Julian, Naren and Ditlev

    One year of hosted·ai: AMA with James, Julian, Naren and Ditlev

    We celebrated our first anniversary in August 2025. To mark the occasion, we hosted our four co-founders for a coffee and chat. We touched upon their journey so far, the service provider industry, and their aspirations with hosted·ai.

  • hosted·ai and Maerifa form strategic partnership to provide a one-stop shop for Neocloud creation at scale

    hosted·ai and Maerifa form strategic partnership to provide a one-stop shop for Neocloud creation at scale

    Santa Clara, CA – 30th September 2025 – hosted·ai has signed a strategic partnership with Maerifa Solutions, a leading digital infrastructure company focused on the provision of technology design, deployment and supply chain management services. The partnership aims to facilitate the rapid creation and scaling of Neoclouds – cloud services built around GPU infrastructure for AI – by providing a one-stop shop for infrastructure advice, hardware, procurement and finance, and efficient, profitable GPU orchestration using hosted·ai software.

    Maerifa simplifies Neocloud creation through its relationships with AI cloud infrastructure OEMs such as NVIDIA, Supermicro and Lenovo, and supply chain and finance partners who can support hardware procurement and purchasing. With hosted·ai, Maerifa can now also provide turnkey software for Neocloud orchestration and monetization, with easy-to-use tools for GPU cloud service design, pricing, metering, billing and self-service.

    “The demand for GPU infrastructure is growing by leaps and bounds, however, there remains little focus developing multi-faceted Neoclouds with the ability to deliver the full catalogue of this infrastructure to end customers in a way that is economically viable long-term. Together with hosted.ai we have a solution that enables rapid scalability and will provide these companies with a way of focusing on what they are best at, attracting customers and providing innovative software solutions. We are already working on a number of projects together and invite others looking to grow their platforms to see how we can help,” said Rahul Kumar, Senior Executive Officer, Maerifa Solutions.

    “There is huge demand for AI training and inference infrastructure, but Neoclouds face quite a few challenges to deliver the scale that the market needs,” said Narendar Shankar, Chief Commercial Officer at hosted·ai. “Our partnership with Maerifa is exciting news for companies in this space, because they now have one expert partner for sourcing and delivering GPU infrastructure, and getting help with financing; and combined with hosted·ai, the software to manage, provision and bill for AI cloud services while making those services efficient and profitable.”

    hosted.ai was founded to make GPU cloud efficient, easy and profitable for service providers, by creating a turnkey GPUaaS platform designed specifically for companies in this market. hosted.ai was launched in 2024 by a team with deep experience of owning, running, and building solutions for AI and for service providers, at businesses including VMware, Nvidia, Expedia, XenSource, OnApp, Sunlight and UK2.

    Maerifa Solutions was conceived, incubated and launched by Aethlius Holdings to create an ecosystem of Tier-1 partners across Digital Infrastructure and related financing solutions delivered by its partners to address the funding gap of acquiring hard-to-access GPU server technology. Since its launch in Q3 2024 it has already partnered with leading players in the industry and is in discussions to deliver multi-million dollars’ worth of hardware and associated solutions to projects in Europe, Middle East, Africa and Southeast Asia.

    About hosted·ai
    hosted·ai provides software to make AI infrastructure hosting simple and profitable for service providers. The hosted·ai platform is a turnkey AI cloud / GPUaaS stack that gives service providers the tools they need to create, manage and monetize GPU cloud infrastructure. hosted·ai was founded in 2024, launched publicly in 2025 and has teams across the US, EMEA and Asia-Pacific. For more information, visit https://hosted.ai. 


    About Maerifa Solutions
    Maerifa Solutions is an ADGM-registered digital infrastructure company, in collaboration with its extensive ecosystem, brings expertise in technology design and deployment, supply chain management, data centers, and power solutions. This, combined with Maerifa Solutions’ deep financial acumen, enables it to deliver creative investment solutions that help clients realise the full potential of AI infrastructure. By offering innovative funding mechanisms and access to hardware and hosting capacity, Maerifa Solutions ensures the long-term scalability and capital efficiency of AI projects.

  • FuriosaAI and hosted·ai Form Strategic Partnership to Deliver Industry-Leading AI Infrastructure Powered by Tensor Contraction Processors

    FuriosaAI and hosted·ai Form Strategic Partnership to Deliver Industry-Leading AI Infrastructure Powered by Tensor Contraction Processors

    Redefining price/performance/power for AI cloud deployments with next-generation inference hardware

    Santa Clara, CA – 8th July 2025 – FuriosaAI, a pioneering leader in next-gen AI semiconductor, today announced a strategic partnership with hosted·ai to deliver ultra-efficient, high-performance AI infrastructure built on Furiosa’s Tensor Contraction Processor (TCP) architecture. The hosted·ai cloud platform will fully support Furiosa’s flagship RNGD (pronounced “Renegade”) processors, enabling service providers to leverage TCP-powered infrastructure for hosting AI workloads. 

    hosted·ai is a turnkey AI cloud platform for service providers. It delivers multi-tenant virtualization of infrastructure for AI inference and training, with full software-defined control and oversubscription of hardware accelerators such as RNGD and GPUs. This enables service providers to pool the resources of multiple accelerators, provision those resources on demand to multiple clients, and sell 4x-10x the physical capacity available. As a result they can price their offerings competitively and improve unit economics, achieving higher revenue with an increasing average margin.

    The new partnership will add support for Furiosa’s flagship RNGD Processor for LLM and agentic AI inference to the hosted·ai platform. RNGD leverages Furiosa’s Tensor Contraction Processor (TCP) chip architecture, which solves the fundamental hardware challenge of running AI algorithms: providing not just raw compute power, but also using that compute effectively and efficiently to deliver excellent real-world performance. 

    “We’re excited by this partnership and its potential to transform the cost and impact of AI infrastructure,” said Furiosa’s SVP of Product and Business, Alex Liu. “Furiosa’s processors are purpose-built for AI and represent a huge leap forward in performance per watt compared to GPUs thanks to our Tensor Contraction Processor (TCP) architecture. hosted·ai has the same devotion to efficiency and performance in its AI cloud software stack, enabling service providers to properly virtualize the accelerator and maximize utilization. This unique combination delivers the best solution for sovereign service provider AI clouds.” 

    “This partnership is an important step in our mission to make AI infrastructure accessible and affordable for service providers and their customers,” said Ditlev Bredahl, CEO of hosted·ai. “Together we’ll bring new ways for service providers to accelerate AI workloads with reduced hardware CAPEX and OPEX, optimal utilization, sustainable profitability for their business, and the best price/performance for their customers.”

    Availability of Furiosa RNGD support in the hosted·ai platform is expected by the end of 2025. Looking ahead, the two companies plan to develop an off-the-shelf appliance for service provider AI cloud, combining hosted·ai software, Furiosa accelerators, and rack server modules for easy turnkey adoption by service providers.

    About hosted·ai
    hosted·ai provides software to make AI infrastructure and GPUaaS simple and profitable for service providers. The hosted·ai platform fully virtualizes AI datacenter infrastructure, including GPUs and other hardware accelerators. This makes it possible to share and utilize 100% of hardware resources with users in a secure multi-tenant environment, which reduces the overall hardware requirement, minimizes idle resources, and dramatically changes the cost/revenue/margin equation for AI cloud service providers. For more information, visit https://hosted.ai.  

    About furiosa.ai
    FuriosaAI is building a new class of AI processor for enterprise and data center workloads. Powered by the Tensor Contraction Processor (TCP) architecture, Furiosa delivers sustainable, high-efficiency AI compute designed from the ground up for modern inference applications. Its mission is to democratize powerful AI through AI-native designed ASICs and software stack, giving everyone on Earth access to powerful AI. For more information, please visit furiosa.ai.

  • Software-Defined GPU

    Software-Defined GPU

    Software-Defined GPU

    Making GPUaaS work for service providers and the mainstream AI hosting market

    You’re not virtualizing GPU the wrong way – you’re just not doing it the optimal way for maximum utilization, flexibility and ROI from your hardware investments.

    This high-level whitepaper explains the difference between GPU virtualization and true GPU as a Service (GPUaaS).

    It explores the benefits and drawbacks of GPU passthrough, instancing and slicing, and explains why service provider GPUaaS requires a different approach – especially for AI inference workloads. To get your free copy, just fill out the form.

    Contents

    Why GPU virtualization ≠ GPUaaS

    What does service provider GPUaaS need?

    Software-Defined GPU requirements

    hosted·ai GPUaaS architecture

    hosted·ai hyperconverged platform

    Standalone GPUaaS with hosted·ai

    More information

  • Three GPUaaS playbooks for service providers

    Three GPUaaS playbooks for service providers

    Three GPUaaS playbooks for service providers

    GPU-as-a-Service is a huge opportunity for the cloud hosting industry – but what kind of GPUaaS should you launch to compete, grow and make serious money selling AI hosting? In this 30-minute session we explore three go-to-market playbooks for GPUaaS. Fill out the form to watch it now.

    Speakers:

    Ditlev Bredahl

    CEO

    hosted·ai

    Narendar Shankar

    CCO

    hosted·ai

    What will you learn?

    We’ll give you a quick introduction to hosted.ai, and how it overcomes the drawbacks of the way that GPU cloud is built and sold today. Then, we’ll focus on the opportunities this creates for service providers to fill those gaps in the market, with three suggested GPUaaS playbooks:

    Developer-Focused GPUaaS: why not build a DigitalOcean for GenAI? Here’s how we’d do it.

    SLA-Focused GPUaaS: the Neoclouds might be super-rich, but their service levels don’t make sense. You can do better, of course.

    By The Numbers: in today’s GPUaaS market there is a LOT of space to adjust price and margin in your favor, in your customers’ favor, or both.

  • Three GPUaaS playbooks for service providers – webinar replay

    GPU-as-a-Service is a huge opportunity for the cloud hosting industry – but what kind of GPUaaS should you launch to compete, grow and make serious money selling AI hosting? In this 30-minute session we explore three go-to-market playbooks for GPUaaS.

    Speakers:

    Ditlev Bredahl

    CEO

    hosted·ai

    Narendar Shankar

    CCO

    hosted·ai

    What will you learn?

    We’ll give you a quick introduction to hosted·ai, and how it overcomes the drawbacks of the way that GPU cloud is built and sold today. Then, we’ll focus on the opportunities this creates for service providers to fill those gaps in the market, with three suggested GPUaaS playbooks:

    Developer-Focused GPUaaS: why not build a DigitalOcean for GenAI? Here’s how we’d do it.

    SLA-Focused GPUaaS: the Neoclouds might be super-rich, but their service levels don’t make sense. You can do better, of course.

    By The Numbers: in today’s GPUaaS market there is a LOT of space to adjust price and margin in your favor, in your customers’ favor, or both.