Put AI to work on your own data with Azure AI.
Azure AI lets you build assistants, search and document automation on your own data, inside your own Azure environment. We help you start with a safe, useful first project.
What Azure AI Services covers
What is Azure AI Services?
Azure AI is the group of Microsoft cloud services for building AI into your own applications and processes. Azure OpenAI Service provides advanced language models through Azure. Azure AI Foundry is the platform for building, testing and managing AI applications. Other services handle search, documents, speech and vision.
Unlike a public chatbot, these services run inside your Azure subscription, under your security and network controls. Microsoft states that your prompts and data are not used to train the underlying models, and you choose the region and the access rules.
AI projects succeed when they start with a clear business problem and good data, not with the technology. We help you pick a small project, prove the value and then scale.
A common pattern is retrieval augmented generation. Your documents are indexed in Azure AI Search, and when a user asks a question, the system finds the relevant passages and gives them to the language model to answer with references. The result is an assistant that answers from your content, not from the open internet.
Model availability, features and regions change often, so design decisions are checked against current Azure documentation for your region.
What Azure AI Services can do.
Azure OpenAI Service
Access to advanced language and embedding models in your own Azure environment.
Azure AI Foundry
A platform to build, evaluate, deploy and monitor AI applications and agents.
Azure AI Search
Search across your documents and data, the backbone of assistants grounded in your content.
Document Intelligence
Extract text, tables and fields from invoices, forms and contracts.
Speech, language and vision
Transcription, translation, classification and image analysis.
Content safety
Filters and controls that reduce harmful or inappropriate output.
Private networking and identity
Private endpoints and Entra ID access so AI services are not exposed publicly.
Monitoring and cost controls
Track usage, quality and spend.
How Azure AI Services works.
Choose a use case
Pick a clear task with measurable value and available data.
Prepare data
Organize, clean and secure the content the AI will use.
Build and test
Create the solution, evaluate answers and add safeguards.
Deploy and govern
Roll out with access controls, monitoring and cost limits.
What happens behind the scenes.
Documents are processed and split into passages, converted into numerical representations called embeddings, and stored in a search index. When a question arrives, Azure AI Search finds the best matching passages, and the application sends them with the question to the model.
The application controls what the model sees, adds instructions and checks outputs. Access is limited by identity and network rules, and logs record usage. Evaluation tests measure accuracy so changes can be checked before release.
How it benefits your business.
The impact depends on the use case, but typical wins are time saved finding information, faster document processing and consistent answers to common questions. Staff spend less time searching and retyping, and more on judgement and customers.
Building on Azure keeps control with you. Data stays inside your tenant under your policies, which matters for client confidentiality, privacy law and industry rules.
Starting small keeps risk and cost low. A single, well scoped project produces evidence and experience that guide the next one.
The benefits at a glance.
Answers from your own content
Assistants grounded in your documents.
Faster document handling
Extract data from forms and invoices.
Control and privacy
Your tenant, your region, your rules.
Start small
Prove value with one project.
Governed and monitored
Usage, quality and cost visible.
Integrates with Microsoft 365
Teams, SharePoint and Power Platform.
Pricing: Usage based billing, typically by the amount of text or data processed, with options for provisioned capacity. Costs depend on model, volume and region. Azure prices and features change, so we confirm current pricing and design to a budget before you commit.
What this looks like day to day.
A professional firm has thousands of policy and procedure documents. Infinity builds an internal assistant using Azure AI Search and Azure OpenAI over the firm’s SharePoint content. Staff ask questions in Teams and get answers with links to the source documents. Access follows existing permissions.
This is an illustrative example of how the service is used, not a description of a specific client.
Mistakes we see, and how we avoid them.
Starting with the technology
Pick a business problem first.
Poor quality data
Outdated, duplicated or overshared documents lead to poor answers and leaks.
No evaluation
Test answers against real questions before launch.
Ignoring cost and usage
Unlimited use can run up charges. Set limits and monitor.
Azure AI Services with Infinity.
AI opportunity workshop
Identify and rank use cases by value and risk.
Learn moreData and permission readiness
Clean up content and access before AI sees it.
Learn moreBuild and pilot
Assistants, search and document automation.
Learn moreSecure deployment
Private networking, identity and content safety.
Learn moreGovernance and policies
Usage rules and monitoring.
Learn moreTraining and support
Help staff use and trust the tools.
Learn moreIs our data used to train the models?
Microsoft states that data you send to Azure OpenAI is not used to train the underlying models. We confirm current terms for your deployment.
How is this different from Microsoft 365 Copilot?
Copilot is a ready made assistant inside Microsoft 365. Azure AI is for building custom solutions on your own data and processes. Many businesses use both.
Can the AI see only what each user may see?
It can, when designed with permissions in mind. We build access controls into the solution.
What does a first project cost?
It depends on scope. We aim for a small pilot with a defined budget, and track usage costs.
Can it work with Canadian data residency?
Often yes, depending on which models and services are available in Canadian regions. We confirm before designing.
Talk to us about Azure AI Services.
Book a free consultation. We will look at your current setup and show you where it fits.
Tell us about your IT.
We answer almost every inquiry within one business day.