Typical early-stage product funnels need to test a wide set of candidates--and this is expensive. We've found the root cause to be that we don't know which mechanisms will fulfill product requirements. Should a tastier strawberry produce more sugar or more flavor compounds? Nucleus drops losing candidates using in-silico simulation to reduce early stage testing.

Typical product funnels require many successive phases of testing--and this is slow. We've found the root cause to be that mechanisms are entangled with each other and with the environment. Was this strawberry variety really tastier, or was it just a good year? Nucleus allows you to advance earlier by learning to disentangle mechanisms. It does this by combining your testing data with a simulation model built on a catalog of causal mechanisms mined from the academic literature.

The Nucleus platform automatically quantifies price elasticity from historical data. Product teams use Nucleus optimizers and what-if scenarios to confidently plan promos that hit sales targets while preserving margin.

The Nucleus platform automatically quantifies how every ad dollar drives incremental sales, including the effects of saturation, awareness and interaction with promos and season. Media teams can right-size and reallocate budgets to boost profits.