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eTechBridge

Cloud and AI

Cloud and AI engineering

We design and build cloud platforms and AI features that hold up under security review. We work Azure first, and design around AWS or Google Cloud where your platform already runs there.

Diagram: an Azure landing zone with identity, networking, apps, AI services and data, connected to AWS or Google Cloud where you already run, with policy, monitoring and cost control across them.AzureLanding zoneIdentityNetworkingAppsAI servicesDataOther cloudsAWSGoogle CloudPolicyMonitoringCost control

Where teams get stuck

Security and compliance are blocking AI features

We build AI inside your own Azure tenant, with data protection, private networking and audit logging in place from the first day.

The AI pilot works in a demo and stalls

We find what is holding it back (data, integration, security or cost) and fix it.

The platform was not built for the next stage

We review the architecture, agree what has to change, from identity and networking to deployment and cost, and help you change it in planned steps.

Who we work with

  • SaaS and technology companies building on Azure
  • Health, fintech, legal and HR software teams that handle sensitive data
  • Teams with an AI pilot that needs to reach production
  • Microsoft partners and IT consultancies that need senior cloud and AI delivery

What we do

  • Cloud architecture

    Azure landing zones, identity, networking and environments designed for your workload and documented so your team can change them. Where you also run on AWS or Google Cloud, we design across both.

  • AI applications and agents

    AI features and agents built with Azure OpenAI, Microsoft Foundry and Foundry Agent Service, connected to your own data and tools (including through MCP), and evaluated before release.

  • SaaS and application engineering

    Multi-tenant SaaS architecture, backend and API engineering, system integration and full-stack development, usually as part of a larger engagement.

  • Modernisation

    Moving applications onto managed cloud services and modernising older systems in planned stages, without stopping delivery.

How we work

  1. Discover.

    We learn your goals, your constraints and where the system stands today.

  2. Architect.

    We agree the technical approach, the scope and a fixed plan before any build starts.

  3. Engineer.

    We build, integrate and secure it, with security and data protection included from the beginning.

  4. Enable.

    We document the work and train your team to run it, so you are not dependent on us.

Planning an AI feature, or unsure about your cloud setup?

Tell us what you are working on. The first call is 30 minutes, and you will leave with a clear next step.