AI Engineering

Beyond the demo.
Into the work.

Deploy agents that work with your systems. Give your data and BI engineers the tools to build with AI.

AI in your workflows.
AI in how you build.

Two ways to put AI to work

Put agents to work.

Turn a defined use case into an agent that works with your data and systems, with explicit boundaries and human oversight.

ContextYour data and your definitions

ToolsApproved systems and approved actions

ControlEvaluation, review, and monitoring

Discuss agent deployment

Give your engineers
more capacity.

Put AI into real data engineering and BI development, with the context, testing, and review practices that make it trustworthy.

Data pipelinesBuild and test SQL, notebooks, transformations

Data modelsShared definitions and semantic models

BI developmentCreate and validate measures and reports

Discuss AI-assisted development

Choose around the work

Copilot. Claude. Codex.
Which fits your team?

We compare the relevant products against your actual tasks, then help you implement the choice. Microsoft Foundry and custom agents are part of the conversation where they fit.

Task fit

Can it do the work you actually need?

Integration

Does it fit your Fabric, code, and systems?

Control

Can you test, review, and govern it?

Economics

Do licensing and running costs make sense?

Fabric + agentic AI

Give your agents a dependable foundation.

Clear data definitions. Approved interfaces. Appropriate permissions. We engineer how agents work with Fabric-backed data and how development agents work with your data assets.

Explore Fabric data foundations

Illustrative read-only agent contract

“Why did margin change?”

Context: Approved margin measure and reporting period
Access: Verified caller and permitted accounts
Tools: Read governed metrics and supporting evidence
Control: Show sources. Ask for clarification when needed.

The agent explains the evidence. It cannot change a planning record without a separately approved action.

What should AI help you get done?

Start with one useful workflow, or one real engineering bottleneck.

Discuss your project

Beyond the demo.Into the work.

AI in your workflows.AI in how you build.