Every Build engagement, VeUP's fixed-scope, fixed-price engineering programme, maps to one of three specialisms.
Each one solves a specific problem. None of them are generalist. Cloud Foundation. Sovereign AI. Agentic AI. Senior engineers, start to finish. 60-90 days to production. Written guarantee in every contract.
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The infrastructure problems we see most often.
Legacy systems blocking the AI and modernisation roadmap
On-premise core systems, outdated VPC architecture. The roadmap exists. The foundation does not support it.
AWS spend growing without explanation
No WAR has been done. No FinOps layer. We find 15-45% in recoverable spend in 30 days before a line of Cloud Foundation work begins.
A migration that feels too expensive and too risky
MAP funding covers most migration costs for eligible workloads. The savings from Ignite cover the rest. Zero downtime architecture. Written guarantee.
Compliance requirements the current architecture was never built for
SOC 2, HIPAA, FCA, GDPR, NCUA. Compliance-ready architecture is designed in from the start, not retrofitted.
The foundations your Roadmap depends on.
AWS landing zone designed for your environment and compliance requirements- MAP-funded migration where eligible
- Umbrella deployed from day one for resource-level cost visibility
- FinOps practices built into the architecture, not added later
- Well-Architected Review completed and documented
- 60-90 days to production. Written guarantee.
Best for companies building on legacy infrastructure or building from scratch:
The compliance deadlock.
Every regulated company faces the same situation
AI tools that would make a meaningful difference, blocked because customer, patient, or financial data cannot be sent to a public model.
The deadlock is not caused by regulation.
It is caused by architecture. Sovereign AI runs entirely within your AWS account. Nothing leaves your environment. The compliance question is answered by design, not by exception.
The architecture regulated AI requires.
- Private AI infrastructure on Amazon Bedrock, running inside your AWS account
- Zero data egress: no customer, patient, or financial data sent to a public model
- HIPAA-aligned architecture for healthcare environments
- SOC 2 Type 1-aligned for financial services
- FCA and GDPR-compatible architecture for regulated Fintech
- NCUA-aligned for credit unions
- Production-grade. 60-90 days. Written guarantee.
How is this different from just using Bedrock ourselves?
Amazon Bedrock is the right foundation. What Sovereign AI adds is the architecture around it: data pipelines, access controls, compliance guardrails, integration with existing systems, and the assurance that what goes to production passes the audit. Most teams get a Bedrock demo working in a day. The gap between that and a system a CISO will sign off on is where this specialism lives.
Who it's best for:
The proof of concept problem.
Every company we speak to has an AI proof of concept. Most have three. They work in the demo. They do not ship.
The reason is not the model.
It is everything around the model: the data pipelines that feed it, the architecture that supports it at scale, the compliance layer that allows it to touch real data, and the operational infrastructure that keeps it running when it leaves the test environment.
Agentic AI systems are not chatbots.
They take actions, make decisions, and orchestrate multiple models to complete complex workflows. The difference between an Agentic AI system and a Copilot is the difference between an employee and an autocomplete. We build the former.
The architecture regulated AI requires.
- Production-grade agentic systems on Amazon Bedrock
- Multi-agent orchestration: multiple AI agents working on complex workflows
- RAG pipelines: AI that reads and reasons over your proprietary documents and knowledge bases
- LLM workflows designed for scale, compliance, and real operational environments
- AWS GenAI Competency certified delivery
- Zero data egress where required (connects to Sovereign AI for regulated environments)
- 60-90 days to production. Written guarantee.
Industry use cases:
- Fintech
Document AI, research knowledge bases, compliance workflow automation.
- Healthcare
Clinical protocol access, prior authorisation AI, R&D acceleration.
- Media & Gaming
Content discovery, recommendation engines, player personalisation, LiveOps AI.
- ISV
Agentic features embedded in your product that win enterprise RFPs.