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Use case
DQC for Product Master Data
Shift from manual checks and isolated cleanup to proactively taking control of your product master data with DQC AI and human oversight.
Customer success.
More than 50 leading enterprisesimprove their data with DQC.
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Christoph MaterneHead of Technology MedTech Germany
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“This is not a data project for us. It's a revenue protection and commercial efficiency project.”
+60% better CRM data quality
AI-driven enrichment of 48,000 CRM records – no IT resources needed.
200h+
“DQC gave us clear visibility of missing and inconsistent persistent identifiers in our data, supporting more consistent and scalable improvements. It was also a pleasure working with a collaborative, highly pragmatic DQC team.”
200h+ saved annually through automated matching and agentic workflows
Institutional CRM records enriched automatically, with manual effort limited to exception review.
JGJames GoodingHead of Data and Analytics, IOP Publishing
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“Quantity and quality are often mutually exclusive. But by using the DQC Platform, we've managed to combine the two and improve both at the same time.”
20x faster quote delivery – from weeks to under 24 hours
Autonomous product data enrichment for 2,000 new products per year.
Bastian TauschProduct Owner Digital TEC, Balluff
“We were able to identify and realize hidden revenue potential totaling over €1 million. The implementation took just a few hours and was completed within three weeks. Since every euro recovered directly impacts EBIT, we were able to measurably increase our earnings with the help of the DQC Revenue Integrity Guard.”
€1m+ underbilling identified in top customer contracts
Revenue leakage detected across complex contract, billing and consumption data — implementation in hours, completed within three weeks.
Director Finance
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Making data AI-ready.
Use case
DQC for Finance Data
Stop cleaning up finance master and transactional data in reactive, one-off efforts. Automatically stay on top of your finance data quality.
Use case
DQC for Sales Data
Stop manually checking and correcting customer master and sales transactional data in one-off projects.
Use case
DQC for HR Data
Move beyond one-time manual fixes for bad HR data. Instead, ensure automatically and continuously clean, reliable HR data.