Technology · Azure OpenAI

Azure OpenAI development

If your company runs on Microsoft 365 and Azure, Azure OpenAI is usually the easiest way to get GPT models approved by security and procurement.

  • Senior engineers on every project
  • Evaluation before launch, not after
  • You own the code and the models
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5.0 on Clutch·200+ projects·Production AI in 3 to 8 weeks

In short

The quick answer

We build assistants, copilots and document search on it, inside your own Azure tenant, connected to the SharePoint, Teams and SQL data you already have.

What we build

What we build with Azure OpenAI

Internal knowledge assistants

Search and Q&A over SharePoint, OneDrive and policy libraries using Azure AI Search, with answers that link back to the source document.

Copilots inside existing tools

Assistants that live in Teams or inside your line-of-business apps, so people do not have to open yet another tool.

Document processing

Invoices, claims and forms read with Azure Document Intelligence and GPT, then validated and posted to your systems.

Power Platform add-ons

GPT steps inside Power Automate flows and Power Apps when the logic is too fuzzy for rules.

Fit

Is Azure OpenAI the right choice?

When it is a good fit

  • You are a Microsoft shop and want the model inside your Azure subscription.
  • Security or compliance needs data residency in a specific Azure region.
  • Your content lives in SharePoint, Teams and SQL Server.

When we would suggest something else

  • You need the very newest OpenAI model the day it launches. Azure availability can lag, and regional capacity varies.
  • You are not on Azure at all. The plain OpenAI API is simpler to start with.

Process

How a project usually runs

  1. 01

    Check access and region

    We confirm which models are available in your Azure region and quota before designing around them.

  2. 02

    Map the data

    Which SharePoint sites and libraries matter, who is allowed to see what, and how permissions should carry through to answers.

  3. 03

    Build with evaluation

    A test set of real questions with known answers, run on every change.

  4. 04

    Deploy in your tenant

    Infrastructure as code, private networking where needed, and handover to your Azure team.

Pitfalls

What usually goes wrong

We have seen these enough times to plan around them from the start.

  • Ignoring document permissions, so the assistant shows people content they should not see. We filter by user access.
  • Indexing every SharePoint site at once. Start with the libraries people actually search.
  • Underestimating quota. Request it early, because it can hold up a launch.

Next step

Want to see similar work? Browse our case studies or tell us what you are working on.

FAQ

Azure OpenAI: common questions

Ask us something else
What is the difference between Azure OpenAI and the OpenAI API?

The models are largely the same. Azure OpenAI runs inside your Azure subscription with Microsoft enterprise terms, private networking and regional hosting. The OpenAI API is quicker to start with and gets new models first.

Can it respect SharePoint permissions?

Yes, if it is built for it. We carry user permissions into search so people only get answers from documents they can already open.

Do we need Microsoft Copilot licences as well?

No. Microsoft 365 Copilot is a separate product. A custom Azure OpenAI build makes sense when you need your own workflows, data sources or controls that Copilot does not cover.

How long does it take?

A first assistant over a defined set of documents typically takes 3 to 8 weeks.

Keep reading

Related pricing and decision guides

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