AI Data Readiness & Quality
Your AI will only ever be as good as what's underneath it.
What is AI Data Readiness & Quality?
This is the unglamorous one, and it's usually the one that matters. Models are commodities now. Your data isn't.
We profile what you've actually got, across ERPs, plant systems and the spreadsheets everyone pretends aren't load-bearing. We score it for completeness, duplication, validity and freshness, then help you fix the parts that block the use case you care about.
It won't make bad data good by itself. Someone still has to decide which of your three customer records is the real one. What it does is show you exactly where the rot is and stop the guessing.
Services provided
What the data says
Ask when a data catalog was last accurate and the honest answer is usually "about a quarter ago".
In groups running several businesses, the same supplier commonly exists three times under three different codes. Nobody notices until the AI starts confidently adding them up.
You can get a readiness score before connecting a single system. It's a cheap way to find out whether the rest is worth doing.
Related reading
- Technology & AI
Building a Data Strategy That Actually Works: Five Principles
Five principles for building a data strategy that actually works, what generative AI changes, and a 90-day plan that starts from business decisions.
- Technology & AI
AI-Ready Data: What It Actually Takes
What AI-ready data means in practice: ownership, fit-for-purpose quality, permissions, unstructured content, lineage and privacy, one use case at a time.
- Business Strategy
Are You Actually AI-Ready? A Practical Readiness Check
What an AI readiness assessment should cover: five dimensions, the evidence to gather, common mistakes and how to turn a score into a costed plan.
Where Ganexa stands out
We don't just hand you a report of problems. Fixing them is the engagement.
Golden records you can argue with. When two values conflict we show why one won, and you get to overrule it.
We'll scope it to one use case. Boiling the ocean on data quality is how these programmes die.
Your engagement roadmap
Score it
About 20 minutesA weighted questionnaire gives you a readiness score across six dimensions before anything is connected.
A board-ready score and a prioritised roadmap.
Connect and profile
1–2 weeksWe connect the sources that matter, crawl the schemas, profile every field and flag anything sensitive.
A searchable catalog with lineage.
Clean up
2–6 weeksStandardise codes against the taxonomies your industry actually uses, and deduplicate the entities that appear in more than one place.
A harmonised catalog and reconciled golden records.
Keep it honest
OngoingRules run continuously, so quality is monitored rather than rediscovered in a panic six months later.
Live quality scoring and issue routing.
Built for where you are
Groups with several businesses
"Three business units, three ERPs, and the same supplier in all of them under different names."
We master data inside each unit and reconcile across them, so a shared supplier becomes one record at group level.
One version of the customer and supplier list.
Anyone about to start an AI project
"We're two weeks from a pilot and nobody can tell me if the data is any good."
The assessment answers that in about twenty minutes, and the profiling gives you the detail behind it.
You find out before the pilot, not during.
Regulated manufacturers
"Our substance and compliance data lives in spreadsheets and reporting is manual."
We link the data, harmonise it to the relevant taxonomies, and profile it for the gaps.
Reporting that doesn't depend on one person's spreadsheet.
What you walk away with
Readiness score and roadmap
Where you stand across six dimensions, and what to do about it.
Data catalog with lineage
Searchable, field-level profiling on every connected source.
Quality engine
Configurable rules scoring completeness, uniqueness, validity, consistency, accuracy and freshness.
Golden records
Deduplicated customers, suppliers and materials, with survivorship you can inspect.
PII flagging
Sensitive data found and marked before it ends up in a prompt.
Ready to put AI Data Readiness & Quality to work?
Book a free 30-minute discovery call, you'll leave with a clear, costed next step, no obligation. Or ask us anything: we reply within one business day.
Questions we get asked about AI Data Readiness & Quality
Do we have to connect our systems before we get a score?
No. A weighted questionnaire gives you a readiness score across six dimensions in about twenty minutes, before anything is connected.
Which sources can be profiled?
ERPs, plant systems and the spreadsheets teams quietly depend on. Every field in the sources that matter is profiled for completeness, uniqueness, validity, consistency and freshness.
Do you fix the data or only report on it?
Fixing is the engagement. Codes are standardised against the taxonomies your industry uses, duplicate customers, suppliers and materials are reconciled into golden records, and rules keep scoring quality continuously afterwards.
How is sensitive data handled?
Personal and sensitive data is flagged during profiling, before it can reach a model or a prompt.