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 ↗Data operations
Duplicate Record Review:
Duplicate Record Review:
plan the implementation.
Help data stewards investigate candidates without making destructive automatic merges.
DISCOVERYAnswer the questions
Answer the questions
that shape the build.
Which identifiers are reliable? What would be lost in a merge? How can an incorrect decision be reversed?
Never merge solely on a name similarity score. Protect personal information and preserve distinct legal entities.
We use these answers to agree on integration boundaries, responsible reviewers, access controls and a definition of done. The proposal identifies dependencies and what is included before implementation begins.
FIRST IMPLEMENTATIONProve the useful part.
Prove the useful part.
Then expand deliberately.
Pilot a labeled dataset with both true duplicates and similar but distinct records.
Measure the result
Measure false matches, missed duplicates, lost relationships and review effort.
Prepare for everyday operation
Execute accepted merges through the system's supported process and retain an audit trail.
Document the owner, support path and recovery procedure. Define how the workflow behaves when information is incomplete, access fails or a reviewer declines the proposed result. Agree on what needs fresh validation after a model or integration change.
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.
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.