> ## Documentation Index
> Fetch the complete documentation index at: https://docs.exterview.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Outcome Intelligence

> Coming soon: post-hire outcome intelligence in Exterview with D30, D60, and D90 quality-of-hire signals that will feed back into rubric calibration and evaluation design.

## Purpose

<Info>
  Outcome Intelligence is not available yet. We're building this feature; it is
  not on your account today.
</Info>

Outcome Intelligence will connect evaluation results with downstream hiring outcomes over time — closing the loop between who you evaluated and how they actually performed.

## What it will draw on

<CardGroup cols={2}>
  <Card title="Evaluation results" icon="file-chart-column">
    The scores and reports produced during hiring.
  </Card>

  <Card title="Post-hire signals" icon="seedling">
    D30/D60/D90 check-ins and manager feedback, where configured.
  </Card>
</CardGroup>

## What it will improve

Once built, the loop will feed back into your own configuration — never a shared or cross-customer model:

<CardGroup cols={3}>
  <Card title="Rubric calibration" icon="scale-balanced">
    Tune scoring dimensions based on what actually predicted success.
  </Card>

  <Card title="Evaluation design" icon="bullseye">
    Refine which stages and questions carry real signal.
  </Card>

  <Card title="Future evaluation quality" icon="arrow-trend-up">
    Each cycle sharpens the next — the advantage compounds for your organization.
  </Card>
</CardGroup>

<Info>
  This learning will be scoped to your organization only. Your outcomes will
  improve your evaluations — Exterview will not pool your data into a shared
  model.
</Info>

## Human review, every step

This will never be a fully automatic loop. Two separate checks will always sit between a suggestion and an actual change to your configuration:

```mermaid theme={null}
%%{init: {'theme':'base','themeVariables':{'primaryColor':'#EEF2FF','primaryBorderColor':'#4B6CFE','primaryTextColor':'#0F172A','lineColor':'#64748B','clusterBkg':'#F8FAFC','clusterBorder':'#E2E8F0'}}}%%
flowchart LR
  A([Suggested change]) --> B([Human review]) --> C([Quality check]) --> D([Applied])
```

<CardGroup cols={2}>
  <Card title="A person picks the suggestion" icon="user-check">
    Someone on your team will review a suggested change and choose whether to act on it. Nothing is applied automatically.
  </Card>

  <Card title="A separate quality check must also pass" icon="shield-check">
    Even after a person approves a suggestion, an automatic quality check will still need to pass before the change actually takes effect.
  </Card>
</CardGroup>

## FAQs

<AccordionGroup>
  <Accordion title="Is this available today?">
    No. Outcome Intelligence is coming soon and is not on your account yet. This page describes what we're building.
  </Accordion>

  <Accordion title="Will our outcome data be shared with other customers?">
    No. Outcome Intelligence will be scoped to your organization only. Your data
    will improve your own evaluations only.
  </Accordion>

  <Accordion title="Will the system re-decide past hires?">
    No. Outcome signals will inform future evaluation quality; they won't reverse
    past decisions.
  </Accordion>

  <Accordion title="Will every suggested change happen automatically?">
    No. A person on your team will always review and choose whether to act on a
    suggestion, and a separate automatic quality check will also need to pass
    before anything changes.
  </Accordion>

  <Accordion title="Will we need to supply post-hire data?">
    The loop will work best with post-hire input (check-ins, manager feedback), configured to fit your process.
  </Accordion>
</AccordionGroup>

## Related

<CardGroup cols={2}>
  <Card title="Calibration" icon="scale-balanced" href="/monitor/calibration">
    How feedback from outcomes turns into versioned rubric changes.
  </Card>

  <Card title="Evaluation Design" icon="bullseye" href="/best-practices/evaluation-design">
    Design evaluations the outcome loop can actually improve.
  </Card>
</CardGroup>