Public case studies on AI-supported product systems, decision support, customer experience, QA, and human-in-the-loop workflows.
These case studies summarize product thinking and lessons learned from selected projects without exposing private code, customer data, credentials, or internal business logic.
| Case Study | Product Theme | Focus |
|---|---|---|
| QA-Inn | AI-supported QA testing console | Local execution, evidence-based QA, human-in-the-loop test automation |
| CX-Inn | AI-supported B2B customer experience platform | Signal-first CX, zero-survey intelligence, churn risk, human-in-the-loop action |
| Talent-Inn | AI-supported recruitment and candidate operations | Bulk CV intake, open-role matching, preliminary scoring, CV verification, evidence-led interviews |
The common thread across these case studies is not AI as automation alone.
The focus is AI as a product layer that helps teams:
- structure scattered signals,
- reduce operational friction,
- improve decision quality,
- make work more measurable,
- keep human judgment and accountability in the right place.