Data Cleansing with AI: Clean Data as the Foundation for AI

Many companies want to get started with AI and then realise their own data isn't ready for it. That was the case for an established real estate company. Together we cleaned up its customer and property data with AI.

The starting point

Over the years, large amounts of customer and property data had piled up across different systems. Much of it was incomplete, outdated or duplicated.

This slowed down daily work, because information was hard to find. It also slowed down every idea for digitalisation and AI. After all, an AI is only as good as the data it works with.

The solution: an automated cleanup process

Together we developed an automated data cleanup process.

• Duplicate and outdated entries removed: Duplicates and obsolete records were detected and cleaned up.
• Gaps filled: Missing information was added.
• Data verified: An AI assistant verified existing records against external platforms.
• Rules for the future: Clear rules make sure new entries are consistent from the start.

The result

Today there is one central, structured data set. It's faster to access and stays clean for good.

• One source for everyone: All departments work with the same, up-to-date data.
• Ready for AI: The data is the foundation for automation, analytics and AI-supported customer service.
• Leaner processes: New records are entered cleanly and automatically, which saves rework.

What you can take away

Before you invest in big AI projects, take a look at your data. A cleanup is often the fastest way to measurable value. It makes every further project easier.

At aiworx, a digital colleague takes on this kind of cleanup and keeps things tidy afterwards. If you want to know where your data stands, book a free intro call.