Simple, efficient and sustainable AI infrastructure, built by AlloComp and Lablup
Together with AlloComp, Lablup turns powerful infrastructure into shared AI environments that are easy to access, share and manage.
Learn more about Backend.AIMaking AI infrastructure simple, efficient and more sustainable
AlloComp is an independent AI infrastructure specialist based in Ireland, helping organisations plan, source, deploy and optimise the systems needed for AI, HPC and advanced workloads. From personal AI systems and GPU workstations to multi-node clusters and AI factories, AlloComp brings together the right compute, storage, networking and cooling to deliver the performance, control and efficiency each organisation needs.
AlloComp takes a workload-led approach. By right-sizing each system and optimising every layer, from data management and GPU scheduling to power and cooling, it helps customers improve performance and efficiency, retain control of their AI, support data sovereignty and scale sustainably as demand grows.
Desktop AI
GPU Servers
AI Factories
From powerful hardware to a shared AI platform
Physical infrastructure — compute, storage, networking, power and cooling — is only the foundation of an effective AI environment. To get the most from this valuable hardware, organisations also need a practical way to give users access, allocate resources, manage workloads and understand how their infrastructure is being used.
Lablup’s Backend.AI provides this operating and orchestration layer, managing users, workloads and shared GPU resources. Together, AlloComp and Lablup improve GPU utilisation and make powerful computing resources easier to access, share and manage across users, teams and workloads.
Universities, enterprises, research organisations and AI service providers move from owning GPU systems to operating a secure, usable and scalable AI platform.
The AI infrastructure stack by Lablup and AlloComp
AI infrastructure operating platform
One platform for adopting and operating AI on shared infrastructure
Controlled access to shared resources
Gives each user the right share of GPU systems and clusters
Workload scheduling and orchestration
Schedules jobs across the cluster to raise GPU utilisation
Fine-grained resource allocation
Fractional GPU allocation matched to each workload
On-prem, cloud and hybrid management
Operates every environment with one platform
User access, governance and monitoring
Access control, governance and usage visibility in one place
Support for different accelerators
Runs NVIDIA and other accelerator technologies side by side
Workload and infrastructure assessment
Assesses workloads, users, data requirements and growth plans
GPU workstations, servers and clusters
From personal AI systems to multi-node clusters and AI factories
Compute, storage and networking integration
Selects and integrates the right hardware for each requirement
Power, cooling and facility planning
Plans rack density, cooling and facility readiness from the start
On-premises, colocation and hybrid design
Designs the deployment model that fits each organisation
Deployment coordination and lifecycle support
Coordinates technology partners, suppliers and specialist providers
Independent hardware selection
Vendor-neutral advice across the complete stack
AI infrastructure shared across users, teams and customers
For universities and research organisations, enterprise AI development teams, and regional AI infrastructure and service providers such as data centres and innovation hubs.
Shared university AI platform
Students, researchers and multiple faculties get controlled access to centrally managed GPU infrastructure.
Enterprise AI development platform
Experimentation, model training and inference with access controls and resource allocation across AI development teams.
Sovereign and private AI
Sensitive AI workloads operate within an organisation’s own infrastructure or a trusted regional facility.
AI factory or regional GPU service
Infrastructure allocated across customers, projects and teams, with usage monitoring and room to grow in users, nodes and workloads.
Industry accelerator hubs
Startups get controlled access to centrally managed GPU infrastructure.
HPC and scientific computing
Simulation, analytics and research workloads run alongside AI on the same shared infrastructure.
From infrastructure design to intelligent operation
AlloComp incorporates Backend.AI requirements into the infrastructure design process from the outset — assessing each customer’s workloads, users, data, facilities and growth plans, then designing the compute, storage, networking, power and cooling around how the environment will be accessed, shared and managed.
Working with Lablup, AlloComp identifies suitable Backend.AI use cases, designs shared AI environments around expected users and workloads, and selects and configures compatible GPU systems, storage and networking. Resource sharing, workload scheduling and future expansion are planned in from the start, across on-premises, colocation, air-gapped and hybrid architectures. AlloComp coordinates hardware deployment and Backend.AI implementation, staying a local point of contact from design through deployment and ongoing development — so customers can scale from an initial GPU system to a larger shared platform.
Optimised AI infrastructure, intelligently operated. AlloComp and Lablup help organisations deploy, share and scale AI environments with confidence.
“The value of AI infrastructure is not defined by the hardware alone, but by how effectively people can access and use it. By working with Lablup, we can help organisations design shared AI environments that are powerful, manageable and ready to scale.
“Backend.AI turns GPUs at any scale into one platform people can actually share, and AlloComp adds the workload-led engineering that gets the physical foundation right. Together we deliver shared AI environments across Europe that are efficient, sovereign and ready to grow.
Make AI infrastructure simple, efficient and sustainable.
Meet AlloComp, Lablup’s partner across Europe.
