Your team owns the build.
Start with AI workflow training and the Factory Line source package. Workshop support is available when you need feedback.
Explore the $2,500 package ↗Prepare likely duplicate records for careful review using explicit identity evidence.
Similar names or addresses can represent different people or businesses, while the same entity may appear under several valid names.
Help data stewards investigate candidates without making destructive automatic merges.
A data owner approves a duplicate review for a defined record type.
Suggest candidate groups with the evidence for and against a match.
A data steward verifies identity and approves any merge, including which history and relationships must survive.
Never merge solely on a name similarity score. Protect personal information and preserve distinct legal entities.
Measure false matches, missed duplicates, lost relationships and review effort.
Before expanding the workflow, compare the result with the current process. Include review effort and exceptions in that comparison so the improvement reflects the team's actual experience.
Read the implementation guide ↗The workflow stays centered on your business. The engagement determines who learns, implements and operates it.
Start with AI workflow training and the Factory Line source package. Workshop support is available when you need feedback.
Explore the $2,500 package ↗Get everything in DIY, three months of workshops, weekly team sessions and direct implementation coaching.
Explore guided implementation ↗Include all the learning and guidance, with ownership of agreed operations and major implementation decisions.
Explore managed delivery ↗Prepare a review queue for data-quality issues with clear ownership, source evidence and downstream context.
Explore this solution ↗Bring a process, a bottleneck, or an idea. We'll help you decide what to automate, what to keep under human review, and where to begin.