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Microsoft business solutions

Azure OpenAI & Azure AI services

Microsoft's kit for building your own AI apps: OpenAI and other models, plus search, speech, vision and documents.

  • AI platform (PaaS)
  • Typical project: 3–8 weeks
  • Microsoft

Overview

Where Copilot is a finished product, Azure AI is the kit for building your own. Azure OpenAI runs OpenAI's models inside your Azure tenancy, with private networking and Microsoft's enterprise commitments; a model catalogue adds models from other providers.

Around the models sit services for search (the backbone of knowledge assistants), speech, translation, vision, document extraction and content safety, so most enterprise AI use cases can be built in one place.

Names you'll meet

  • Azure OpenAI
  • Azure AI Search
  • Document Intelligence
  • LangChain
  • Python

What's inside

  1. 1

    Models

    GPT and other models, deployed in the regions you choose.

  2. 2

    Azure AI Search

    Keyword and vector search over your content, for RAG.

  3. 3

    Document Intelligence

    Extract fields and tables from forms and invoices.

  4. 4

    Speech & translation

    Transcription, voice and translation services.

  5. 5

    Content Safety & evaluation

    Filter harmful content and score answer quality.

Is it right for you?

Best for

  • AI features inside your own customer-facing apps
  • Knowledge assistants over large document sets
  • Organisations whose data and security already live in Azure

Think twice if…

  • A packaged product (Microsoft 365 Copilot, Copilot Studio) already does the job
  • You have no engineers to run and monitor AI apps in production

Typical projects

  1. AI proof of value3–8 weeks
  2. Production knowledge assistant (RAG)8–20 weeks
  3. Document processing pipeline8–16 weeks

Typical ranges, not quotes. Scope, data and team size move them most.

Roles you'll hire

  • Azure AI engineer
  • Solution architect
  • Data engineer
Browse available talent

Questions to ask a vendor

  1. 1Which models and regions will you use, and why?
  2. 2How will you evaluate and monitor answer quality?
  3. 3How will you keep running costs predictable?
  4. 4How is our data isolated and protected?

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