Regulators require data to stay in-country.
What it costsPublic AI services are ruled out, and projects stop.
What changesSovereign and in-region architecture, with private models where they are needed.
Agentic OS · ContextAI Transformation · Cloud and AI Infrastructure
Where your AI runs, who can see it, and what it costs.
AI needs infrastructure your security team trusts and your CFO can predict. We migrate and modernise your applications, keep data in the regions your regulators require, set up private AI where public models are not an option, and keep cloud costs under control.
Six parts, one platform
- MigrateTo Azure, AWS or GCP
- ResidencyData kept where rules require
- ModerniseMonoliths to services
- DevOpsCI/CD and platform engineering
- FinOpsCosts you can predict
- Private AIGPU and private model hosting
Built in your cloud accounts, run by us or by you
Written for
CIOs, CTOs, CISOs and heads of infrastructure, and CFOs watching cloud and AI spend
The question you came with
Where should our AI run, how do we keep data in-country, and how do we control the cost?
Part of Enterprise AI Transformation
Where it runs. The data platform, models and agents run here, in the regions your regulators require, at a cost finance can predict.
See the whole programmeWhat is holding your infrastructure back
If two of these are true, the rest of this page is about you.
The cloud bill grows faster than usage.
What it costsFinance loses trust, and AI spend gets questioned too.
What changesFinOps: tagging, rightsizing, commitments and a monthly cost report by team and product.
Agentic OS · PulseOld applications cannot connect to anything.
What it costsAgents cannot reach the data or actions they need.
What changesApplications modernised step by step, with APIs agents and other systems can use.
Agentic OS · AgentsReleases are slow and risky.
What it costsFixes and improvements wait weeks.
What changesCI/CD pipelines, infrastructure as code and monitoring, so changes ship safely and often.
Agentic OS · LoopThe stack, from data to agent
What sits under every agent, and who controls each layer.
- Layer 01 · Region
Where the data lives
Regions chosen by regulation, with residency enforced by policy, not by habit.
- Layer 02 · Platform
Compute, storage and network
Built as code, monitored, backed up and recoverable, in your accounts.
- Layer 03 · Models
Public, private or both
Public AI services where allowed, private models where not, behind one controlled gateway.
- Layer 04 · Operations
Run, cost and improve
Monitoring, incident response, cost reports and regular reviews, by us or your team.
What we build
The capability on the left, what your team would notice on the right.
- Migration
Cloud migration
Applications and data moved to Azure, AWS or GCP in planned waves, with rollback for each.
- Residency
Data residency and sovereign cloud
Architecture that keeps regulated data in the required region, with access and encryption your auditors can check.
- Modernisation
Application modernisation
Monoliths broken into services where it pays, and APIs added so agents and systems can connect.
- DevOps
CI/CD and platform engineering
Pipelines, infrastructure as code, environments and guardrails your engineers can self-serve.
- FinOps
Cloud cost optimisation
Spend visible by team and product, waste removed, and commitments planned against real usage.
- Private AI
GPU and private AI infrastructure
Private model hosting and GPU capacity for workloads that cannot use public AI services.
What stays yours
We build and hand over
- Infrastructure as code and architecture documents
- Pipelines, runbooks and recovery plans
- Cost reports and tagging standards
You keep and control
- Your cloud accounts and contracts
- Your data and encryption keys
- Admin access, in your name
How an engagement runs
The same four steps whatever we build. The first one is small, fixed-fee and useful on its own.
Start with a fixed-scope offer
A fixed scope, a set timeline and a deliverable you keep. The quickest way to start.
Pilot
Private and Sovereign AI Setup
AI that runs in your region, on infrastructure you control, behind one governed gateway
- Time
- 6 to 8 weeks
- Price
- Fixed fee, agreed on a call
- For
- CIOs, CISOs and risk leaders in regulated industries
The problem. Regulators or data sensitivity rule out public AI services, so AI projects stop at the security review.
What happens, week by week
- Weeks 1 to 2Classify the workloads
Which AI uses can run on public services, which need in-region services, and which need private models.
- Weeks 3 to 5Build the platform
In-region cloud or private GPU infrastructure, a model gateway, access control and logging.
- Week 6Deploy the models
Private or in-region models deployed and evaluated against your use cases.
- Weeks 7 to 8Hand over and run
Runbooks, cost model and monitoring, run by your team or by Pegasus Run.
You get
- Workload classification by data sensitivity
- In-region or private AI platform
- A governed model gateway with logging
- Cost model and runbooks
Who signs off
CISO and CIO, with risk and the DPO
What we need from you
Cloud or data centre access, a list of AI use cases, and security requirements
Not sure where to start? Begin with the AI Transformation Review: two to three weeks, $1,500, credited to month one.
Questions
Which clouds do you work with?
Azure, AWS and Google Cloud, including in-country regions wherever your regulators require them.
Do we need private AI models?
Only where regulation or data sensitivity rules out public services. The Private and Sovereign AI Setup offer tells you which workloads need them.
Can you run our cloud after migration?
Yes. Managed operations cover monitoring, backup, recovery and cost reviews each month, or we hand over to your team.
How does this connect to AI Transformation?
It is where the agents, data platform and models run. Getting residency, access and cost right early prevents AI projects stopping at the security review.
Keep going
Where Cloud and AI Infrastructure fits your industry, what to read next, and the tools involved.
Industries we do this in
Playbooks
Tools we review for this
AI transformation for the agentic engine era
Start with a fixed-fee AI transformation review. We map your systems, data and teams against the six layers of Pegasus Agentic OS and name the first workflows to hand to agents. You keep the findings whether or not you work with us.