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Solutions / AI Readiness and Data

Data

Get your data ready before AI asks for it.

AI is only as useful as the data underneath it. We help you find out where your data lives, who owns it, and what needs to be fixed before it can support AI in production.

Discuss your AI readiness

Why it matters

Every AI project eventually runs into the same question: can we trust the data? Data is often spread across applications, file shares, and cloud services, with no single owner and no clear record of where it came from.

We help you build a working picture of your data before you build on it. That means knowing what you have, who is responsible for it, how it moves, and what needs to be fixed so it can support reporting, analytics, and AI in production.

What we hear
“We have data everywhere, and no one can tell us which version is right.”
“Our AI pilot worked on a clean sample, then stalled on real data.”
“Nobody owns the data, so nobody fixes it.”

What we deliver

Data discovery and inventory
Find and catalog the data you hold across applications, databases, file shares, and cloud services.
Data quality and ownership
Assess quality against how the data will be used, and name accountable owners for the data that matters most.
Pipelines and integration
Design and build the pipelines that move data reliably between systems, on premises and in the cloud.
Data governance and access
Set the rules for who can use which data, and put the access controls in place to enforce them.

What changes

A clear picture of the data you have and where it lives
Named owners for the data that matters
Data you can trust enough to build on

How we deliver

01
Plan
We learn your environment, your goals, and your constraints before we propose anything.
02
Design
We design the solution around how your business runs and the requirements you have to meet.
03
Deploy
We build, test, and deploy it, wherever the work needs to happen.
04
Manage
Where it is in scope, we keep it running and improving after launch.

Technology we work with

See all partners

Part of our relationships with over 80 technology manufacturers. We recommend what fits your environment, not a single vendor.

Snowflake
Microsoft Azure
Google Cloud
AWS
Datadog
Kognitos

Questions we get asked

Do we need to fix all of our data before we start using AI?
No. We focus on the data your first use cases depend on, fix what matters for those, and build the habits and tooling that make the next use case easier.
Can you work with the data platforms we already have?
Yes. We start from your current platforms and only recommend changes where they block what you are trying to do.
How do we start?
We start with a discussion of your priorities and the data behind them, then agree the discovery and remediation work in scope.

More from AI Readiness and Data

One team across every solution, so the work stays connected.

Platforms
Compute, storage, and cloud platforms sized for AI workloads.
Controls
Access, privacy, and usage guardrails in place before AI goes live.
AI Readiness
A clear view of what has to be true before AI reaches production.

Connected practices

Cloud Engineering
Private, hybrid, and public cloud designed to be operated, not just launched.
Cybersecurity
Security across endpoint, identity, cloud, and applications, connected to the environment it protects.
Core Infrastructure
Network, compute, storage, data center, and workplace technology, including rack and technology integration.
Managed Services
Day-to-day operations and support from people who know your environment.

Let's talk about what you're building next.

Tell us what you're planning, where the work needs to happen, and what's getting in the way.

Discuss your AI readiness