Most supply chain systems track and report. In aerospace, defense, and industrial operations — where dependencies cascade and a wrong call has real consequences — operators need options, tradeoffs, and consequences filtered by real constraints, not another status feed.
I worked with the founding team to translate deep operational expertise into product direction: decision intelligence built around constraints, viable scenarios, and pilots validated against decisions operators had actually faced — not synthetic demos.
Outcomes.
New category defined
Decision intelligence for supply chain — distinct from tracking and visibility tools, with market language and testable MVP architecture.
Constraint-grounded trust
Operators reported the system understood their world — viable options first, not every theoretical possibility.
Pilots in high-stakes contexts
Gas turbine and aerospace scenario retrospectives confirmed decision support beat status tracking when tradeoffs were real.
What the full case covers
- Decision-support problem framing and competitive context
- Research scenarios, constraint insights, and category choice
- Vantive solution, workflow, design artifacts, outcomes, and reflection