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Service

Data, AI & Copilot

AI is only as good as the data underneath it. We build the lakehouse, model the semantics, then deploy Copilot and custom agents where they measurably shorten a real workflow.

What clients typically see

Reporting cycle time
Days to hours
Reporting cycle time
Copilot weekly active use
> 65%
Copilot weekly active use
Support deflection
30–50%
Support deflection

Ranges drawn from comparable engagements. We agree the baseline and the measurement method with you during discovery, before anything is promised in a statement of work.

Capabilities

What the engagement covers

Scope is assembled from these, sized to your estate. You are never charged for a workstream you do not need.

  • Microsoft Fabric lakehouse and warehouse design
  • Power BI semantic models and executive reporting
  • Microsoft 365 Copilot readiness and rollout
  • Custom copilots and agents on Azure AI Foundry
  • Retrieval-augmented generation over enterprise content
  • AI governance, evaluation, and cost controls

Delivery path

How the work runs

A typical shape. Phases compress or extend with the size of your estate, and each one ends in something you can review.

  1. 01

    Readiness

    Data estate, permissions, and Copilot licence assessment.

  2. 02

    Foundation

    Lakehouse, governed semantic layer, and access model.

  3. 03

    Pilot

    One high-value use case, measured against a baseline.

  4. 04

    Scale

    Rollout, evaluation harness, and ongoing cost governance.

Start with a conversation about your estate

Thirty minutes with a consultant who has delivered data, ai & copilot before. You will leave with a view on sequence, effort, and whether this is the right place to spend the budget at all.