You’ve been mandated to scale AI, so you launch AI principles, ethics statements and governance forums across your organisation. That’s the easy part.
The hard part comes when real AI use case needs real data and no one can confidently say “yes” to simple questions: Is this dataset safe? Compliant? Enough for this model? And if something goes wrong, who takes the risk?
Our Data Readiness solution for safe and responsible AI is how you get the answers.
We take the rules you’ve already agreed and apply them directly to the data your AI is actually using. Dataset by dataset. Use case by use case. Until you can clearly see what’s ready, what isn’t and what needs fixing.
AI doesn’t fail because organisations lack ambition. It fails because the data is stuck in limbo.
This is what we see all the time:
To move AI from labs into delivery, the data readiness gap has to close.
This isn’t a report. It’s working clarity.
This is not:
This is the work that makes it usable.
We keep this simple and grounded in reality to match desired outcomes.
Get clarity on what’s usable and what isn’t.
You leave this phase knowing:
Which data your AI use cases actually depend on
What “ready” means for each dataset
Where the risks sit across quality, privacy, compliance, control
What needs fixing first
The outcome: a shared view of the truth.
Data you can confidently approve for AI.
This is where policy turns into evidence.
AI-relevant data discovered and properly classified
Sensitive data protected before it’s used
Quality validated against model intent
Datasets explicitly approved for training or inference
The outcome: approved data with clear traceability.
Data Readiness that scales with your AI ambition.
We help you make sure this doesn’t become another one-off exercise.
A repeatable readiness workflow
Clear ownership and decision points
Scoring and prioritisation that drives action
Automation where it removes friction
The outcome: deliver the next AI use case without starting from scratch.
Ortecha are my go-to partner and have never failed to deliver.
— Head of Data, Rathbones
We work at the data layer every day. We know what AI needs to scale and how to get you there without ripping up your programme.
What we bring to your organisation:
Data Readiness for AI is the process of making specific datasets safe, compliant, high-quality and approved for use in AI models.
It applies your existing AI governance policies directly to the data feeding your models. That includes validating data quality, assessing privacy and security risk, confirming ownership, and establishing clear lineage and provenance at dataset level.
The outcome is evidence-based approval of which data can be used for training or inference, under what conditions, and why, so AI can move from pilot to production with confidence.
For regulated industries, Data Readiness provides defensible documentation and traceability to meet regulatory scrutiny and demonstrate responsible AI use.
Not at all.
It’s the difference between agreeing the rules and proving the data meets them.
Especially then. Strong governance creates clear standards, but without operational execution at dataset level, AI teams still get blocked.
Data Readiness is what turns governance from theory into usable evidence.
Quite the opposite. Closing the data readiness gap removes ambiguity.
Instead of repeated sign-offs and risk debates, teams get a clear view of what’s approved, what needs remediation, and what can move forward.
The result? AI initiatives shipped responsibly, safely and faster, time and time again.
Yes, absolutely. We assess provenance, licensing, sensitivity and fitness for purpose before the data is used. That includes evaluating bias risk, compliance exposure and alignment to your internal policies.
Not at all. It’s designed as a repeatable capability.
As new AI use cases emerge for your organisation, the same readiness model can be applied, so each initiative doesn’t start from zero.
Your partner for every step.
Get out of AI starting blocks, without hesitation
Turn scattered activity into a single vision and clear direction
Make data & AI know-how your team's superpower
Practical thinking from people delivering data, AI and technology.
