Outcome pillar · Evolve

Artificial Intelligence

AI becomes valuable when it is grounded in secure infrastructure.

The position

Grounded in secure infrastructure, or it does not go to production.

The interesting question is never the model. It is where the data sits, who is allowed to see it, what happens to the answer, and whether anyone can explain the whole chain to an auditor eighteen months later.

AI infrastructure simulator

Size the hardware for your model before you buy it.

Pick an open-weight model, how many people use it at once and how long their conversations run. See which servers run it, how fast, what the rack draws and what it costs to run in the UAE. Every spec is checked against the vendor datasheet.

  • 35 open models, including K2 Horizon, Jais and Falcon
  • NVIDIA, AMD, Intel and Huawei accelerators
  • Inference, fine-tuning, post-training and training
Open the simulator

Portfolio scope

What is inside this domain

  1. Readiness and use-case advisory

    Where AI would genuinely remove work, what it costs to run at your volume, and what has to be true about the data first. Including an honest list of the use cases that are not worth automating yet.

  2. Secure AI infrastructure and data foundations

    On-premises or sovereign hosting where residency matters, network segmentation, identity and access, and retention and audit applied to prompts and outputs the same way they are applied to documents.

  3. Enterprise knowledge assistants

    Assistants grounded in your own approved material, answering with a citation back to the source document, and inheriting the permissions of the person asking rather than a service account.

  4. Document intelligence and workflow automation

    Extraction from invoices, contracts, forms and correspondence into the systems that already hold the record, with a human confirming anything the model is not confident about.

  5. Computer-vision analytics

    For approved security use cases only: occupancy, PPE compliance and restricted-zone alerts running on the CCTV estate you already own, under the same retention and access rules as the footage itself.

What we supply

The whole AI stack, from the accelerator to the application.

Hardware and software from vendors we already supply, sized with the simulator and delivered by our own engineers. Accelerators come inside the OEM servers below. NVIDIA, AMD, Intel or Huawei is decided on your model, your budget and your data-residency position.

GPU servers

Eight-GPU systems for training and large models, and 2U and 4U servers for departmental inference.

Dell
PowerEdge XE9780 and XE9785 (8x NVIDIA B300 or AMD MI355X), XE9685L liquid-cooled (8x B200), XE9680 (8x H200, AMD MI300X or Intel Gaudi 3), XE7745 and XE7740 (8x RTX PRO 6000, H200 NVL, L40S or AMD MI350P), XE9712 (GB300 NVL72 rack).
Lenovo
ThinkSystem SR680a V4 (8x B300), SR650a V4 (up to four double-width GPUs in 2U).
Huawei
Atlas inference servers with Ascend accelerators, where a build standardises on Huawei.

Accelerators

Chosen for the model, not the brand.

NVIDIA
Blackwell Ultra B300 and GB300, B200, H200, RTX PRO 6000 Blackwell, L40S and L4. Rubin from the second half of 2026.
AMD
Instinct MI355X, MI300X and the MI350P PCIe card. The MI400 series as it ships.
Intel
Gaudi 3, in OAM and PCIe form.
Huawei
Ascend 910C and Ascend 950.

Workstations and edge

For development, fine-tuning smaller models and inference beside the people who use it.

HP
Z8 Fury G6i (up to four RTX PRO 6000 Blackwell) and ZGX Nano AI Station (GB10, 128 GB).
Dell
Dell Pro Max with GB10, and Dell Pro Max workstations.
Lenovo
ThinkStation PGX (GB10).

Storage for AI data

Checkpoints, training corpora and the documents an assistant is allowed to read.

Dell
PowerScale all-flash for training data and retrieval.
Huawei
OceanStor for large on-premise data estates.
QNAP, Synology
Departmental storage for knowledge-assistant document sets.

Network and cabling

The GPU fabric, the front-end network and the fibre between them, certified to the standard.

Cisco
Nexus 9000 switching at 400G and 800G for GPU fabrics and front-end networks.
Huawei
CloudEngine data-centre switching.
Ruijie
Data-centre and campus switching.
Norden, Opterna
High-density fibre, copper, racks and containment for GPU rows.

Platform software

Where the models run and how people reach them.

Microsoft
Microsoft 365 Copilot and Copilot Studio, Microsoft Foundry, and Azure Local for Azure services on your own hardware.
Proxmox
Virtualisation with GPU pass-through, on hardware you own.

Security and continuity

Controls around the model, the data and the people who use it.

Fortinet
Segmentation and secure access around the AI cluster.
Veeam
Backup and tested restore for models, vector indexes and source data.
Kaspersky
Endpoint protection on the machines that reach it.

Vision AI

Analytics on the camera estate you already own.

Hikvision
DeepinView and DeepinMind AI cameras and recorders.
Dahua
WizSense and WizMind analytics.
Digifort
Video management with analytics and access-control integration.

Deployed by our engineers vLLM and SGLang for serving, Kubernetes and Slurm for scheduling, and the open-weight models themselves: installed, tuned and supported by UBM.

A vendor named here is one UBM supplies. It is not a claim to an AI-specific vendor badge; authorisation levels are confirmed in writing at quotation.

Open the simulator

Outcomes

What you get out of it

  • A use case with a measurable before and a measurable after.
  • Data boundaries written down before the first pilot, not after the first incident.
  • Nothing in production that cannot be explained to an auditor.

Technology ecosystem

The vendors behind this domain

No third-party product line. This domain is delivered by our own engineers on infrastructure supplied through the other five.

The full technology ecosystem

How we deliver it

The same six stages, applied to this domain

Planning, procurement, deployment, operation, maintenance and disposal are not a separate product. They are how every domain reaches production, stays there, and eventually leaves without becoming somebody’s problem.

  1. 01

    Planning

    Use cases scored on value and feasibility, with a written answer on data residency and access before anything is built.

  2. 02

    Procurement

    Platform and hosting selected against the residency position agreed at planning, with the commercial terms and the running cost at your volume stated before the pilot starts.

  3. 03

    Deployment

    A bounded pilot on real data with the access model set first, measured against the state it replaced.

  4. 04

    Operation

    The assistant is a supported service: prompts logged, sources refreshed, failures raised like any other incident.

  5. 05

    Maintenance

    Usage and accuracy reviewed with the business owner, sources re-indexed, scope extended only once the last extension has proven itself.

  6. 06

    Disposal

    When a use case is retired, the index and the prompt history are deleted on a written schedule and the source data returns to the retention rule it came from.

The full service model

Adjacent domains

03

Software

Software that simplifies collaboration, communication and content.

View domain

04

Security

Physical and logical security operate as one risk posture.

View domain

06

Services

Services make every product accountable over its lifecycle.

View domain

All six domains

Tell us which layer is hurting.

An engineer will look at the environment you actually have before anyone writes a proposal.

Talk to us Industries