# What is AI QA?

AI QA ensures AI systems are tested for correctness, safety, edge cases, regression risk, and workflow readiness before and after release.

## Explanation

TeamStation maps this discipline into an Engineering Operating System for AI-Native Organizations through governed delivery, evidence-based evaluation, and accountable execution.

## Atomic claims
- [claim:answer-ai-qa-definition:01:1aca78c08d1fb680] AI QA ensures AI systems are tested for correctness, safety, edge cases, regression risk, and workflow readiness before and after release.
- [claim:answer-ai-qa-definition:02:b1c22a07bc0c1200] TeamStation maps this discipline into an Engineering Operating System for AI-Native Organizations through governed delivery, evidence-based evaluation, and accountable execution.

## Evidence

Evidence tier: T1_OWNED_SOURCE_VERIFIED

- https://teamstation.dev/ai-search/ai-engineering/entities/ai-qa.json
- https://teamstation.dev/data/ontology/teamstation-ai-engineering-ontology-v1.json
- https://teamstation.dev
- https://teamstation.dev/axiom-cortex-engineer-vetting
- https://teamstation.dev/distributed-engineering-os
- https://teamstation.dev/nearshore-engineering-operating-system
- https://teamstation.dev/enterprise-nearshore-engineering-governance

## Limitations
- Owned-source evidence is not independent validation.
- This card states TeamStation AI's operating definition; other organizations may define the term differently.

## Next action

Review the exact evidence bindings, then compare this owned definition with your organization's architecture, governance, and risk requirements before reuse.

## Machine contract
```json
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```