Ask for fixes in plain English instead of describing every edit manually.
Copilot
Fix data faster with AI that stays under your control.
Copilot helps teams clean up extracted data, propose guided fixes, and move through repetitive review work faster. Suggestions stay visible, approval stays human, and changes remain tied to the workflow.
Where repetitive cleanup slows teams down
Copilot is designed for repetitive correction, not blind automation.
Manual cleanup is slow, especially when the same kinds of fixes keep showing up across rows and batches. Copilot reduces that effort without turning review into a black box.
Review proposed changes before anything is applied.
Speed up repetitive correction work inside the real workflow.
Keep risky values visible instead of hiding them behind automation.
Stay in control of what actually changes in your data.
How teams use Copilot
A guided correction flow, not an autonomous one.
01
Ask for help
Describe what needs fixing in plain English inside review, datasets, or templates.
02
Inspect suggestions
Copilot proposes updates and shows what it wants to change before anything is applied.
03
Approve what makes sense
Apply only the suggested changes your team wants to keep.
04
Keep moving
Use the same review-first pattern across repeated cleanup work without losing control.
Inside the Copilot workflow
What teams use Copilot for today.
Plain-language requests
Describe fixes in the language your team already uses instead of building manual multi-step edits.
Review exceptions first
Copilot helps direct reviewer attention toward low-confidence or risky values that need decisions.
Guided updates
Suggestions are proposed in a structured way so reviewers can inspect the intended result.
Approval-based apply
Changes are not the default. Reviewers stay responsible for what actually gets accepted.
Undo-friendly workflow
Teams can correct course quickly instead of treating every applied suggestion as final.
Cross-surface support
Copilot works across review, datasets, and templates, not as a detached chatbot.
Where it fits
Copilot is an acceleration layer inside the main workflow.
Copilot works where teams already review and refine data.
It is not a separate destination. Copilot speeds up the correction work happening inside Review Studio, dataset management, and template refinement while keeping the same approval model.
Workflow
Documents -> Review (+ Copilot) -> Datasets / Templates -> Exports
Why teams use Copilot
Less repetitive cleanup, more reviewer focus.
Copilot helps teams move through repetitive corrections without removing the review step. That makes it useful for real operations, where trust matters more than automation theater.
What teams gain
Faster review without giving up control.
- Less repetitive editing across rows and batches.
- Faster cleanup in the places where reviewers already work.
- A clearer approval model than fully automatic correction.
- Better reviewer focus on exceptions instead of routine cleanup.
Use AI where it helps most: inside review.
Copilot is designed to make correction work faster, not to replace reviewer judgment. It works best when teams want speed and control at the same time.