When a dataset update should not restart the whole review.
The team has already reviewed a dataset, then receives an appended file, a refreshed benchmark, or a replacement version and needs to know what actually changed.
Dataset Changes
See what changed before retraining, re-evaluating, or appending new data.
Review a new upload against the last approved version, keep prior decisions intact, and send only the changed data through review.
A delta review with history attached.
Datascreen separates new, changed, and duplicate rows, carries forward prior review decisions, and keeps every reviewed version visible in the project timeline.
Product motion: compare against the last reviewed dataset, review only the delta, and preserve the cleaned version history.
Watch walkthrough
Product demo: update a dataset without starting over.
Show the original reviewed dataset, upload a changed file, separate duplicates from new rows, review the delta, and produce the next cleaned version.
How Datascreen keeps dataset updates reviewable.
Detect what changed
Separate the rows that are new, changed, duplicate, or unchanged before review starts.
Skip duplicate review
Carry forward prior decisions when the same row appears again.
Scan only the delta
Focus review effort on changed data while keeping the previous version in context.
Export the next version
Save the cleaned update with a record of what changed and what reviewers decided.
A prioritized list of rows and clusters that deserve human review.
The row, source, neighborhood, and reason shown together.
A record of what reviewers kept, removed, fixed, or escalated.
A workflow-ready handoff that states what was reviewed and what remains uncertain.