Start with a defined trigger
A data owner approves a duplicate review for a defined record type.
Data operations
Duplicate Record Review:
Duplicate Record Review:
the workflow in practice.
Scheduled duplicate check-to-review queue
FROM INPUT TO HANDOFFA clear job
Explore the architecture behind the pattern ↗
A clear job
for every step.
This is a proposed workflow pattern. We confirm data access, permissions, integration options and review ownership with your team before implementation.
Never merge solely on a name similarity score. Protect personal information and preserve distinct legal entities.
Assemble the right context
Collect permitted identity fields, trusted identifiers, source provenance and approved matching criteria.
Perform the bounded task
Suggest candidate groups with the evidence for and against a match.
Review before taking action
A data steward verifies identity and approves any merge, including which history and relationships must survive.
Deliver and record the result
Execute accepted merges through the system's supported process and retain an audit trail.
Build an improvement loop
around real work.
Measure false matches, missed duplicates, lost relationships and review effort.
Keep the input, relevant context, review decision and final result connected. When a reviewer corrects something, use that evidence to improve the instructions or integration, then validate the change against representative cases.
CHOOSE THE RIGHT SUPPORTBuild it. Build with us.
Build it. Build with us.
Or have us manage it.
The workflow stays centered on your business. The engagement determines who learns, implements and operates it.
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 ↗Work through it together.
Get everything in DIY, three months of workshops, weekly team sessions and direct implementation coaching.
Explore guided implementation ↗We manage the foundation.
Include all the learning and guidance, with ownership of agreed operations and major implementation decisions.
Explore managed delivery ↗CONNECTED OPPORTUNITIES
Data Quality Triage
Prepare a review queue for data-quality issues with clear ownership, source evidence and downstream context.
Explore this solution ↗START WITH YOUR WORKWhere is your team
Where is your team
doing too much by hand?
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.