One contract, one accountable partner
From funding and ambition to production workloads
An AI supercomputer is not a server purchase. It is a data centre problem, a networking problem, a storage problem, an identity problem, a scheduling problem and a service-design problem — and it only works when all six are solved by the same team.
We take an organisation from "we have funding and an ambition" to "our researchers, data scientists and engineers are running production workloads on infrastructure we trust" — covering strategy, procurement, liquid-cooled data centre build, fabric engineering, acceptance testing, the full software platform, federated identity, and ongoing 24/7 operations.
Strategy • Procurement • Facilities • Fabric • Platform • Operations
Strategy & Design
Multi-year investment roadmap, workload and demand modelling, reference architecture, formal architecture decision records, and independent design review. We design for a 10–15 year lifecycle with successive expansion tranches, not a single purchase.
What we deliver:
- Desirability, viability and feasibility assessment of each capability
- Reference architecture and formal decision records
- 10–15 year lifecycle design with expansion tranches
Procurement & Supply Chain
Vendor-neutral configuration and competitive sourcing across HPE, Supermicro, NVIDIA, Arista and VAST Data. We maintain a continuously refreshed standing GPU price book to protect you from a volatile market.
What we deliver:
- Continuously refreshed standing GPU price book
- Early warning on component-level supply constraints
- Sector and volume pricing wherever it applies
Data Centre & Facilities
Site selection and readiness, direct liquid cooling (DLC) rack design and CDU integration, power and thermal envelope assessment, and full physical/logical documentation with port-level mapping.
What we deliver:
- Direct liquid cooling for 8-GPU nodes air cooling cannot serve
- Power and thermal envelope assessment
- Structured cabling and cross-connects with port-level mapping
Network & AI Fabric
High-speed Ethernet spine (400G and 800G-class) with lossless RoCEv2 — priority flow control, DCQCN/ECN tuning, and per-rail design. Ethernet-based, so it integrates with your existing network rather than becoming an island.
What we deliver:
- 400G–800G Arista Ethernet spine with RoCEv2
- Segmented VLAN/VRF architecture for cluster, storage and ingress
- Integrates with existing network skills and infrastructure
Commissioning & Acceptance
A formal, staged acceptance programme with published pass criteria at every phase: GPU burn-in, RDMA line-rate verification, collective-communication benchmarks, thermal validation, failover drills, and rehearsed runbooks.
What we deliver:
- GPU burn-in and RDMA line-rate verification
- Collective-communication benchmarks
- Evidence pack and performance baseline for warranty claims
Platform Build
Bare-metal provisioning, custom OS imaging, GPU driver and fabric-manager stack, then a production Kubernetes platform with GitOps deployment and three-environment promotion (dev → UAT → production).
What we deliver:
- Production Kubernetes with GitOps deployment
- Pre-change snapshotting and automated verification
- Any node rebuildable from source in minutes
Shared and Contributed Capacity
The single most useful thing about AI Factory
A central shared pool is funded centrally and open to all approved projects at a base priority. Individual departments, business units or teams can then contribute their own hardware into the same platform — and in return get guaranteed priority on the capacity they funded, plus access to the shared pool when their own kit is idle.
The result: no more stranded GPUs sitting idle under someone's desk, no more capital fights, and one platform, one support model and one security posture instead of a dozen shadow clusters.
Proven at scale • Ethernet not proprietary islands • Service design built in from day one
Why Organisations Choose ASI
We have done the hard parts
Lossless Ethernet AI fabrics, liquid-cooled high-density racks and federated research identity are where these programmes fail. We have working, validated implementations of all three.
AI-assisted delivery
We deploy from intent-based specifications and automation, compressing platform build from days into hours — and giving you a reproducible, documented environment.
Service design, not just infrastructure
Adoption is designed in from day one through user studies and staged access, because a technically perfect platform nobody uses is a failed programme.
Sovereignty built in
Data classification, residency and indigenous data sovereignty requirements are designed into the platform rather than bolted on afterwards.
Standing Up a First or Next-Generation AI Platform?
Best for universities, research institutes, national agencies, health and life-science organisations, and enterprises where data cannot leave the country and the environment must serve many teams at once.