AI and analytics initiatives with no infrastructure to actually run on.

AI and analytics infrastructure architected so your data and AI initiatives have a platform built for them, not a bolt-on.

Data Pipelines Model Hosting AI Infrastructure

Get a AI & Data Analytics solution What's included

Cross-platform

What AI & Data Analytics covers

AI & Data Analytics is about the infrastructure underneath AI and analytics initiatives — data pipelines, model hosting, and the compute those workloads actually need to run reliably — not just the initiative itself. The underlying platforms differ, but unsupported AI infrastructure fails the same way everywhere.

On Microsoft Azure

How we deliver this on Microsoft Azure

The detail below is Azure-specific. As other platforms come online, this same page will show the equivalent approach for whichever platform you select.

Azure AI, Azure OpenAI, Machine Learning, Synapse, and Fabric architected so your data and AI initiatives have a platform built for them, not a bolt-on.

Azure AI Azure OpenAI Machine Learning Synapse Fabric

Signals

This is likely relevant if…

!Data lives scattered across services with no unified analytics platform

!An AI or Azure OpenAI pilot is stuck because the infrastructure underneath isn't ready

!Machine Learning workloads are run ad hoc, without a repeatable pipeline

!No clear data governance for what feeds into AI or analytics workloads

!Synapse or Fabric was stood up but usage never went beyond an initial trial

!Cost of AI/analytics workloads is unpredictable and hard to attribute

How we work

New solution, or fix what you have

Tell us which situation you're in — the consultation is scoped differently depending on the answer.

Path A — Solution design

Nothing's in place yet

You're starting an AI or analytics initiative and need the underlying Azure platform designed correctly.

Data platform architecture designed around Synapse or Fabric
Azure OpenAI or ML infrastructure scoped for the actual use case
Data governance defined before pipelines go live

Path B — Fix / enhance

Something exists but isn't working

An AI or analytics platform exists but isn't scaling, or costs more than it delivers.

Audit of current data and AI infrastructure
Pipeline and compute right-sizing for ML/AI workloads
Cost attribution and governance retrofit

Scope

What's included in the AI & Data Analytics consultation

Data platform architecture review — Synapse, Fabric, or both
Azure OpenAI / Machine Learning infrastructure assessment
Data pipeline design or audit for repeatability
Data governance and access review for AI workloads
Cost attribution model for AI/analytics spend
Scalability review for growing data volumes
Written report ranking fixes by impact
30-minute walkthrough call to review findings

Also relevant

Related Azure domains

Ready to talk about AI & Data Analytics?

Describe what's happening — we'll follow up with a scoped consultation quote within 1 business day.

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