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  • Cloud architecture & managed services

Cloud That Moves at Your Speed

We design, build, and manage cloud infrastructure purpose-built for AI workloads – from strategy and migration through to AIOps, FinOps, and intelligent cloud operations.
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Service Overview

Cloud Engineering Done Right

Multi-Cloud Fluency

Deep capability across AWS, Azure, and GCP - we architect for the right platform for your workload, not the one we happen to prefer.

Security & Compliance First

Zero-trust architecture, IAM governance, and automated compliance monitoring built into every cloud environment from the start.

FinOps Built In

Cost visibility, rightsizing, and spend governance integrated from day one - cloud that scales without budget surprises.

What We Do

Our Areas of Expertise

From cloud strategy and migration through to AIOps, developer platforms, and enterprise-grade security, our Cloud practice covers the full infrastructure and operations lifecycle.

Cloud Strategy & Architecture Consulting

We help you define a cloud strategy that makes AI a first-class citizen from the start - selecting the right cloud AI services, GPU infrastructure, and governance model that scales with your ambitions.

WHAT WE OFFER
  • AI workload readiness assessment: GPU/TPU capacity, latency profiling, and total cost modelling
  • Cloud AI service selection: AWS Bedrock, Azure OpenAI Service, Google Vertex AI, Databricks
  • Hybrid and multi-cloud strategy for AI model serving, data sovereignty, and resilience
  • FinOps for AI: cost governance frameworks for GPU compute and LLM API consumption
  • Cloud AI governance: model access controls, data residency, and compliance architecture

Cloud Migration & Modernisation

We accelerate your journey to the cloud with AI-powered migration tooling and agentic automation - reducing downtime, de-risking data migration, and modernising legacy workloads so you arrive cloud-native and AI-ready.

WHAT WE OFFER
  • AI-assisted dependency analysis and automated migration planning and wave design
  • Intelligent data migration with AI-driven validation, cleansing, and automated reconciliation
  • Legacy workload modernisation: containerisation, refactoring, and re-platforming
  • LLM-generated migration documentation, runbooks, and automated test case creation
  • Post-migration AI performance tuning and autonomous cost optimisation

AIOps & Intelligent Infrastructure

We transform cloud operations with AIOps - deploying AI agents that monitor, diagnose, and remediate infrastructure issues autonomously, reducing mean time to resolution and freeing your teams to focus on innovation.

WHAT WE OFFER
  • AI-powered observability: predictive alerting, anomaly detection, and autonomous root-cause analysis
  • Autonomous incident response agents integrated with PagerDuty, OpsGenie, and Slack
  • Infrastructure as Code with AI-assisted generation and configuration drift remediation
  • Intelligent cost optimisation agents: rightsizing, reserved instance planning, and waste elimination
  • AI-driven capacity planning and dynamic auto-scaling policy generation

DevOps & Platform Engineering

We build the engineering platforms and delivery pipelines that enable your teams to ship software and AI models rapidly, reliably, and safely - embedding intelligence into every stage of the build, test, and release process.

WHAT WE OFFER
  • Internal developer platform (IDP) design and implementation for engineering self-service
  • AI-augmented CI/CD pipelines: intelligent build optimisation, test selection, and deployment risk scoring
  • GitOps and platform engineering with automated environment provisioning and policy enforcement
  • LLMOps pipelines: CI/CD for AI models, prompt versions, and RAG knowledge bases
  • Developer experience tooling: AI coding assistants, automated code review, and documentation generation

AI-Native Cloud Application Platforms

We build the cloud platform layer that makes your AI applications possible at enterprise scale - low-latency LLM inference infrastructure, vector search at scale, and agentic service meshes your AI features depend on in production.

WHAT WE OFFER
  • LLM inference infrastructure: vLLM, TGI, AWS Bedrock, and Azure OpenAI at production scale
  • Vector database deployment and operations at scale (Pinecone, Weaviate, pgvector, Qdrant)
  • Agentic microservices with tool-calling, API orchestration, and event-driven routing
  • AI API gateway: rate limiting, cost controls, model routing, and comprehensive audit logging
  • Serverless Gen AI pipelines with AWS Lambda, Azure Functions, and Google Cloud Run

Cloud Security, Resilience & Compliance

We design cloud environments that are secure, resilient, and compliant by architecture - with automated threat detection, intelligent failover, and continuous compliance monitoring across all major frameworks.

WHAT WE OFFER
  • Zero-trust architecture for AI workloads, model serving, and data access infrastructure
  • Automated compliance monitoring: SOC 2, ISO 27001, HIPAA, GDPR, and DiGA
  • AI-powered threat detection, SIEM integration, and automated security incident response
  • Multi-region active-active and active-passive failover architecture for AI workloads
  • Chaos engineering: AI-driven fault injection to proactively validate resilience posture

TECHNOLOGY & TOOLS

The Stack We Build With

Our cloud engineering capability spans the three major hyperscalers alongside leading infrastructure-as-code, observability, CI/CD, and AI cloud service tooling.
  • Microsoft Azure
  • Amazon Web Services
  • Google Cloud Platform
  • Terraform
  • Pulumi
  • Kubernetes
  • Docker
  • Helm
  • GitHub Actions
  • Azure DevOps
  • GitLab CI
  • ArgoCD
  • Prometheus
  • Grafana
  • Datadog
  • New Relic
  • AWS Bedrock
  • Azure OpenAI Service
  • Google Vertex AI
  • vLLM
  • Pinecone
  • Weaviate
  • AWS Lambda
  • Azure Functions
Our Perspective

How We Think
About Cloud

Three principles that guide every cloud engagement we take on.

Cloud Without an AI Strategy Is Already Behind

Most cloud migrations optimise for cost and agility — and stop there. The organisations extracting the most value are designing cloud architectures specifically for AI workloads from the outset: GPU capacity, low-latency inference, vector search, and LLMOps pipelines built in, not retrofitted later.

FinOps Is Engineering Discipline, Not a Monthly Report

Cloud cost overruns are almost always an engineering architecture problem, not a procurement problem. The most effective FinOps practice is one where cost visibility, rightsizing logic, and governance policies are embedded into the infrastructure codebase — not managed in a separate reporting workflow.

Security Is Architecture, Not a Checklist

Security controls added at the end of a cloud deployment are always weaker than those designed into the architecture from the start. Zero-trust, least-privilege IAM, and automated compliance monitoring need to be first-class engineering concerns – not a final review gate before go-live.
Client Insights

Building things that will last

Together with our clients, we’re shaping an enduring, AI-powered future for healthcare and enterprise.
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Ready to Build Your AI Stack?

Talk to our Data & AI team. We’ll assess your readiness and map a clear path to production-grade AI — governed, scalable, and built for your domain.

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