Transforming manual DDQ work into an AI-assisted workflow
Norric is an AI-native operating system that helps private market firms respond to institutional DDQ and RFP requests, structuring how answers are reused, reviewed, and approved. As a Product Designer Intern, my role wasn't to "add AI," but to design a system where AI supports speed and consistency while humans retain ownership over judgment and risk. This project was about designing boundaries, not automation for its own sake.
ROLE
Product Design Intern
TIMELINE
2025.11 - 2026.01
TEAM
CEO, Front/Back-end developer
IMPACT / OUTCOME
Design system and agentic AI workflows for a $500B+ AUM enterprise platform - Goldman Sachs, Ferrari's owner group, Porsche Ventures.
[ Timeline ]
What began as a weak A/B testing tool lacked real value. Instead of scaling it, I stopped development, returned to users, and reframed the product around their actual decision-making needs. Within five months, the rebuilt version became the foundation of CRM campaigns for 50+ businesses.
[ Problem ]
What began as a weak A/B testing tool lacked real value. Instead of scaling it, I stopped development, returned to users, and reframed the product around their actual decision-making needs. Within five months, the rebuilt version became the foundation of CRM campaigns for 50+ businesses.
Prior answers are scattered across PDFs, desktops, SharePoint, and outdated repositories
60% of DDQ questions repeat
IR teams spend hundreds of hours per quarter searching, copying, and rebuilding content