AI data readiness
Want to use AI? Start with your data.
AI is only as good as what you feed it. If your ERP, your spreadsheets and your other systems don’t agree, AI just gives you wrong answers faster. We get your data clean, connected and trustworthy, so when you’re ready for AI it actually works.
Does this sound like your business?
Maybe you’re not sure where to start. Maybe you know exactly what needs to happen and nobody has the time to do it.
- Your data lives in five places and nobody trusts the numbers.
- The same number is defined three different ways in three departments.
- Somebody ran an AI pilot and nobody believed the output.
- You’re being sold AI tools and can’t tell which would survive contact with your data.
- The knowledge that matters is still in somebody’s head.
What the work involves
The unglamorous part, which is the part that decides whether any of it works.
Start from a real question
Something the business needs answered and can’t answer today. That decides which data has to be trustworthy first, instead of boiling the ocean.
Settle the definitions
One definition per number, agreed across sales, operations and accounting. AI won’t resolve a conflict between three versions. It’ll average them and sound certain.
Connect and clean
ERP, spreadsheets and the systems nobody mentions. Remove the double entry that guarantees two copies will disagree.
Then judge the tools
With trustworthy data, it’s obvious which tools earn their keep and which were a demo. Often the useful answer isn’t AI at all, and we’ll say so.
Questions about AI data readiness
Do I need clean data before using AI in my business?
Yes. AI is only as good as what you feed it. If your ERP, your spreadsheets and your other systems don’t agree, AI just gives you wrong answers faster. Getting your data clean, connected and trustworthy is the work that makes AI useful, and it pays for itself even if you never turn AI on.
Where should a manufacturer start with AI?
Start with a question the business already needs answered and cannot answer today. That tells you which data has to be trustworthy first. Starting with a tool instead of a question is how companies end up paying for a pilot that nobody uses and nobody believes.
What makes data not ready for AI?
The same things that make reporting hard: the same number defined three ways in three departments, records keyed in twice, knowledge that only exists in somebody’s head, and systems that were never connected. AI doesn’t resolve those conflicts. It averages them and states the result confidently.
Is this worth doing if we never adopt AI?
Yes. Clean, connected, agreed data is what reporting, margin analysis and quoting all depend on. The work pays for itself in answers people can trust today, and it means you’re ready if and when an AI tool is actually worth buying.
Tell us what you’d want AI to answer.
We’ll tell you honestly what would have to be true about your data first.