Powerful infrastructure. Connected platforms. Security built in.
With powerful infrastructure, connected platforms and security built in.
Computing capacity, enterprise platforms and security controls need to be considered together. Explore each area and the vendor technologies behind it.
Give AI workloads a solid foundation, from individual workstations to shared enterprise platforms.
Control access, protect AI interactions and keep people accountable as agents take on more work.
Connect AI to useful work, trusted information and the applications your teams already use.
AI can help teams find information, prepare work and act across connected applications. The value comes from giving people dependable tools, clear controls and a practical way to use them.
We bring computing, platforms and security into one proposal, with vendor engineering resources brought in before deployment.
These are common conversations as organisations move from individual tools to connected business applications.
Know which tools people are using and establish approved access to business information.
Explore the approachGive agents defined permissions, accountable owners and a controlled connection to business systems.
Explore the approachConnect AI to authoritative information, with data quality, permissions and evaluation considered together.
Explore the approachProtect prompts, responses and connected workflows against manipulation and sensitive data leakage.
Explore the approachMatch local, private or hybrid platforms to model size, performance, data location and operating costs.
Explore the approachStart with a defined process, an accountable team and a measurable outcome, then plan a repeatable rollout.
Explore the approachThese common starting points show how approved data, controlled access and the right computing platform can come together.
Approved information sources, access controls and answer evaluation built into the design.
Defined permissions, with people retaining sign-off on important decisions.
A workstation or shared platform sized around the software, model and data.
GPU capacity for departments, laboratories and technical teams, with acceptable use and data protection considered from the outset.
Power, cooling, rack density, storage throughput, networking, identity and support determine whether an AI environment performs as intended. We bring each into the design, drawing on the appropriate vendor expertise before deployment.
Begin with a business goal or an existing specification.
Compare hardware, platforms and support with vendor input, with responsibilities and scope agreed from the outset.
Bring supply, preparation and project delivery together around the agreed plan.
Bring a specification, a named product or the work you want AI to improve.
Choosing between an AI PC and a workstation? Read our practical computing guide.
