Komon
Komon analyzes organizational data to rank AI opportunities and flag risks, data gaps, and weak-fit ideas. It helps your team decide what to investigate first — and what to avoid for now.
I built these four working prototypes around real organizational problems.
Komon makes AI initiatives defensible. Noroshi makes external change visible.
Tōgō makes messy data usable. Tsukai makes questions answerable.
Selected Work
Komon analyzes organizational data to rank AI opportunities and flag risks, data gaps, and weak-fit ideas. It helps your team decide what to investigate first — and what to avoid for now.
Noroshi monitors the intersection of AI and the supply-chain landscape, surfacing external signals that may change strategic priorities before they become obvious.
Tōgō prepares messy cross-regional operational data for AI use by cleaning, mapping, and standardizing fragmented inputs into reliable analysis-ready form.
Tsukai lets managers ask operational questions in natural language and receive grounded answers from business data without writing SQL or reading dashboards.