Learning

Build on what the newsroom has learned

Keep editorial decisions, audience context and source evidence useful over time. Feedback Hub, Editorial DNA and expert track records give the next decision a better starting point.

A researcher compares documents and notes at a computer
An editorial standard evolves through judgement

A correction belongs to its story. A recurring pattern may justify a wider change, once the newsroom has reviewed the evidence.

Kaboompics.com / Pexels · Bair Media screen montage

Feedback Hub · Learnings

Find the lessons in repeated editorial choices

Learnings brings recurring edits together by title, desk, channel and role. Inspect the supporting pattern, confidence and recorded use in later articles. Personal writing preferences belong to the journalist’s own DNA profile.

  • Patterns with a recorded history
  • Evidence across desks and roles
  • Application in subsequent work

Editorial decisions

Turn a pattern into a decision the desk can discuss

Return to the editorial choices behind a pattern. Decisions keeps the original AI proposal, the human edit and the outcome together. See who accepted, changed or rejected a proposal, and use the concrete examples in the next editorial review.

  • Original proposal and human edit side by side
  • Editor, reason and outcome
  • Recorded decisions as the basis for review

Editorial DNA, from promise to practice

Define what your title stands for. Compare that promise with the archive and current output, inspect the evidence and follow the same standards across channels.

Put the editorial promise beside the published work

Editorial DNA compares the agreed standard with the archive and current output. Value families make it easier to discuss where a title is keeping its promise and where the evidence calls for attention.

  • Editorial standard and archive baseline
  • Current output and value families
  • Traceable evidence for the comparison

Real dashboard interface with illustrative history. Demo scores are not measured customer results.

An editorial team reviews the finished work together at a screen

Look back at the work itself

Review the story as it appeared, alongside the decisions that shaped it. Evidence gives the newsroom a basis for discussing what should change next time.

Pavel Danilyuk / Pexels

Source knowledge that stays useful

Return to the people you consult and the claims they make, with dated evidence and editorial review.

Experts Database

Know more about a source than their job title

Expertise, source context and earlier predictions sit together in the expert profile. This fictional directory contains 128 experts with individual histories, so the newsroom can assess a source in context.

  • Search by name and field of expertise
  • Dated claims and reviewed outcomes
  • Source decisions tied to a specific claim

Prediction Tracker

Return to a prediction when the evidence arrives

The demo tracks 1,536 fictional predictions. Ishan Desai expected electricity bills to fall by at least 10 per cent; the observed comparison shows a 2.4 per cent rise. The original claim, comparable figures and suggested assessment stay together for human review.

  • A deadline for checking the claim
  • Original source and outcome evidence
  • AI suggestions awaiting editorial confirmation

The memory behind the feedback loop

Newsroom Memory

Earlier decisions and source context remain available for the next story.

Calibration

Reviewed examples provide a reference for evaluating assistance.

Editorial change control

Editors review conflicts and decide which changes belong in the shared standard.

Walk through your own newsroom day

Bring a story and the way your team works. We will walk through the reporting, production and editorial decisions together.

Request a walkthrough
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