CASE STUDIES
These simulations show the full path from Service A assessment to Service B implementation: first identifying where AI changes judgment responsibility, then turning findings into operating rules.
Each case is fictional and designed to explain Insynergy's implementation approach. The cases do not describe actual client engagements or diagnostic results.
SERVICE A / ASSESSMENT CASES
This case shows how to assess Decision Boundary™, human review triggers, and Decision Logs after a financial services firm begins using generative AI in customer-facing and screening-related workflows.
This case shows how to assess responsibility boundaries when AI affects quality classification, equipment alerts, defect hypotheses, and field work procedures.
This case shows how to assess AI's role in organizational positions, legal interpretation, external responses, information management, and evidence.
This case shows how to assess where AI-generated analysis, proposal text, contract issue lists, and deliverable drafts require expert judgment and evidence.
SERVICE B / IMPLEMENTATION CASES
This case shows how a financial services firm can move from an informal AI-use environment to an operational judgment structure for customer responses, complaint triage, sales screening memos, and internal policy lookup.
This case shows how a manufacturer can define AI's role in quality judgment, equipment stop decisions, corrective action, and model-change governance.
This case shows how a public-sector organization can define AI's role in organizational positions, legal interpretation, external responses, information management, and evidence.
This case shows how a professional services firm can define the boundary between AI support and expert judgment in client advice, deliverable quality, contract obligations, and confidentiality.
