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eTechBridge

Cloud and AI

Secure AI Implementation

4 to 6 weeks. Fixed scope.

We build your AI feature with Azure OpenAI or Microsoft Foundry inside your own tenant, with PII and PHI protection, private networking, data residency and audit logging. You also get the architecture document and an estimate of running costs at scale.

Diagram: your app, an AI model and your data running inside a private network in your own Azure tenant, with identity, secrets and audit logging in place.Your Azure tenantPrivate networkYour appAI modelYour dataIdentitySecretsAudit log

Who it is for

  • Product teams in health, fintech, legal and HR software
  • Teams whose AI pilot works in a demo but stalls before production
  • Teams answering customer security questions about how they use AI

What is included

Built in from the start

  • PII and PHI protection
  • Private networking
  • Managed identity
  • Data residency
  • Audit logging
  • Evaluation

What you get

  • The AI feature, running in your own tenant
  • An architecture document
  • A running-cost estimate at scale

How it works

  1. Discover.

    We learn the use case, the data involved and the constraints you work under.

  2. Architect.

    We agree the design, the data flows, the controls and a fixed scope before any build starts.

  3. Build.

    We build the feature with the controls in place and evaluate it against agreed test cases.

  4. Hand over.

    You get the architecture document and the cost estimate, and we take your team through how it runs.

Planning an AI feature?

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