Option 1
Placement review
A decision for one or two workloads.
Cloud & Hosting · Decision guide
Cloud AI, on-premises AI or hybrid: how to choose
Short answer: put AI where the data is allowed to live. Sensitive or regulated data points to on-premises or private in-country hosting; general workloads benefit from cloud scale; most organisations end up hybrid.
1
Classify the data
- Public · internal
- Confidential · secret
2
Check the rules
- PDPL and NCA
- Sector regulator
3
Weigh cost and speed
- Volume
- Latency
4
Place the workload
- Cloud · private · hybrid
The story in one minute
From a familiar problem to a clear result
Delivery flow
- AssessWorkloads, data residency and costs
- DesignLanding zone, identity and network
- BuildInfrastructure as code and security baseline
- MigrateWorkloads moved in planned waves
- RunMonitoring, backup and cost control
Built in from day one
- Data stays in-region
- Access by role
- Encrypted at rest
A typical customerCDO, CIO and CTO · An architecture that will be approved.
- Today
Where should AI run: public cloud, local cloud or inside your data centre?
The wrong choice raises cost, blocks approvals or limits which models you can use.
- What we do
We match each AI workload to the right environment using data sensitivity, cost, latency and regulation.
- What you get
- Placement decision per workload
- Reference architecture
- Cost comparison
- Security and residency position
How we work
Simple steps, one team
- 1
Classify
Rate data and workloads by sensitivity.
- 2
Compare
Weigh cloud, local and hybrid options.
- 3
Design
Draw the target architecture.
- 4
Prove
Test with a real workload.
Option 2
AI hosting strategy
Policy and architecture for all AI.
Option 3
Design and build
We then stand up the environment.
New to a term? Data and AI glossary
Clients
Organisations we work with
Across banking, healthcare, government, retail, energy and telecom.
FAQ
Frequently asked questions
Is on-premises AI as capable as cloud AI?
For most enterprise tasks such as search, summarisation, classification and Arabic document work, right-sized private models perform well. Frontier reasoning is still strongest in the cloud.
Can we start in the cloud and move later?
Yes, if the architecture keeps models swappable. We design for that from the start.
What is hybrid AI?
An architecture where sensitive requests are served by private models and general requests by cloud models, with a router enforcing the policy.
Do you provide private AI hardware?
Yes, through AI in a Box and in-country GPU hosting options.
Topic cluster
Explore the topic cluster
Curated links across our Saudi hubs, sector pages and long-form blog research.