# Turn quality from a sample into an operating loop.

> Define the eligible population, preserve audit evidence, reconcile missed work, and connect recurring findings to coaching and leadership decisions.

## Key Specifications
- **Target Audience:** Quality heads, support operations, and process owners
- **Primary Inquiry:** How do we increase quality coverage without losing explanation and control?

## Core Architecture & Mechanism
### 1. Scope
Define sources, eligibility, scorecard, criteria, and the denominator.

### 2. Evaluate
Audit eligible work and preserve criterion-level rationale and evidence.

### 3. Review
Inspect findings, missed audits, calibration context, and channel patterns.

### 4. Improve
Route coaching and material process drift to the responsible operating role.

## Frequently Asked Questions
### Q: Does OpenOS remove manual QA?
A: No. It changes where human effort is used: scorecard ownership, calibration, evidence review, exceptions, coaching, and process decisions remain essential.

### Q: Can we import historical interactions?
A: Supported controlled imports and ingestion contracts can bring selected chat, email, and audio data into the Quality workflow.

## Claim Boundaries
- Coverage claims always show the configured eligible denominator.
- AI-scored sentiment is not represented as CSAT.
- A finding is evidence for review, not proof that a person or process is at fault.

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Canonical Reference: https://www.openost.com/solutions/quality-operations