Nuclearn Request a meeting
Solution Corrective action

Every condition report,
screened the same way.

Apply your own screening criteria and codes to each incoming condition report, with the reasons shown, and send what the AI isn't sure of to a screener.

For corrective action and performance improvement. The CAP screener and program owner keeps the decision.

The problem

The queue keeps growing. Experienced screeners have limited time.

Incoming reports vary in detail, terminology and context. Screeners have to apply the same site criteria to each one while keeping ownership and trend coding consistent.

  • Repeated manual triage competes with investigation time.
  • Inconsistent coding makes emerging patterns harder to see.
  • A recommendation is only useful when its basis can be checked.
The workflow

How the work gets done.

Nuclearn CAP AI screens each report against your own codes and procedures and shows its reasons. A report moves on when its confidence clears your threshold; the rest, and a random quality sample, go to a screener. Performance Improvement AI then trend-codes the record.

  1. ReceiveRead the incoming report from your CAP system.
  2. ScreenApply your screening criteria, with the reasons shown.
  3. RouteConfident results move on; the rest go to a screener.
  4. RecordEach decision is logged, and results are written back.
  5. TrendTrend-code the record and follow what stands out.

What goes in

  • The condition report and its fields
  • Your screening criteria and codes
  • Past screened reports
  • Your threshold and quality sample rate

What comes out

  • A screened record, written back to your CAP system, with the basis visible.
  • Your screeners keep the screening decision. Only people with screening authority record or change it.
Published field story

Starting where the plant's reporting workload begins.

The situation
In a published account of Nuclearn's early work, the founders describe condition-report triage as a recurring burden for experienced plant staff.
The work
CAP automation supports the screening and coding work, and the public demonstration shows a screening record and the detail behind it.
The result
A repeatable screening process that gives people more of the context they need to review the incoming report.

Read the founders' story → Watch the CAP AI demo on YouTube →

Based on Nuclearn's published account and public demonstration. Results depend on site rules and deployment.

Products

Products that help with this work.

Nuclearn CAP AIWrite a condition report; screening with the reasons shownLearn more → Nuclearn Performance Improvement AICR coding against WANO criteria, and trendsLearn more →
Request a meeting

Bring your own cap screening.

We'll walk through the workflow on public or demo data, and how it would fit your site's process.

Request a meeting