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| # Demo Script | |
| ## 2-Minute Version | |
| I built a forward-deployed AI simulation to mirror how Distyl operates. Instead of starting with a model, I started with an ambiguous enterprise problem: massive noisy support tickets and fragmented workflows make it hard to explain VIP churn drivers. I defined success metrics first, mapped the current workflow, and explicitly decided where AI should vs should not be used. Then I rapidly prototyped a system that turns unstructured tickets, emails, and chat conversations into auditable structured outputs with evidence citations, risk gating, and human review routing. Finally, I built an evaluation harness, documented failure modes, and abstracted the solution into reusable modules so the pattern generalizes to other enterprise workflows. | |
| ## 5-Minute Version | |
| *To be finalized after system is built and measured.* | |
| ## Key Demo Flow | |
| 1. **Problem Scoping** β Show the AI suitability matrix and explicit non-goals | |
| 2. **Prototype Lab** β Process a case bundle end-to-end, inspect structured output | |
| 3. **Reliability & Review** β Show risk gate routing a high-risk case to review queue | |
| 4. **Abstraction Layer** β Walk through reusable modules and adjacent use cases | |