Clean data, without the cleanup job.
The data your firm relies on is rarely as clean as anyone realises.
Inside almost every law firm, the same pattern repeats itself.
Client records duplicate across systems as new integrations come online. Historical matter entries sit in the database long after the underlying information has changed. Spelling variations, abbreviations and inconsistent contact formats accumulate over years until nobody knows quite which version is correct.
None of it is anyone’s fault. All of it carries a cost.
Bad data quietly distorts the work that depends on it. Matter reports run against duplicate client records overstate activity and obscure firm-level trends. Conflict checks and identity verification rest on contact data that nobody is fully confident is accurate. Marketing automations send the same client three identical emails. New systems inherit the mess of the systems that came before them.
And the manual cleanup work that finally gets scheduled into someone’s calendar tends to be the work that gets repeatedly delayed, because it never feels as urgent as the fee-earning work in front of the team that day.
duplicut was built to remove that constraint.
An AI-powered data cleansing and validation tool, built specifically for UK law firms – designed to scan your existing client and matter records, identify the duplicates and inconsistencies your team can’t see manually, help you resolve them through a clear and controllable review process, and then switch on real-time validation against new entries so the problem stops compounding.
It works with the platforms your firm already uses, requires no rip-and-replace, and gives your team a single source of truth without the months of manual effort that data quality projects usually demand.
A clean data workflow,
in four stages.
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2
3
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built to fit your environment, not replace it.
DupliCut is designed to work with the systems your firm already runs.
There is no rip-and-replace requirement, no requirement to migrate data into a new platform, and no demand on your team to learn a separate piece of software to maintain the clean data DupliCut produces.