Enterprise Solutions for Hard Science

Product and R&D teams use the Nucleus platform to optimize product development pipelines by reducing testing and accelerating wins.

Production and operations teams use Nucleus to quantify how product mechanisms drive production variation.

For Product Development

For Manufacturing Technology

Product Development Teams Get Better Results fROm Less Physical Testing

“Super Suit” Architecture of Rich Data & Action Primitives

Our data architecture for enterprise science preserves knowledge crucial to understanding, even with nested/conditional/multimedia structure, that won’t fit in ERP/LIMS/PLM. It provides full control to manipulate the data, with advanced tools like tree-compare, without the limitations of traditional applications.

Simulate performance beyond tested environments

Our environmental simulators and causal model accelerate time-to-market by understanding performance beyond physically tested environments, so we can enrich early successes for those likely to repeat. By focusing on mechanism, we can reduce time spent in multi-phase trials to validate that early results repeat across environments or interacting mechanisms.

Trim Losers Early with Candidate Simulation

Our simulation model and catalog of mechanisms pools the learnings from all of your historical tests to virtually screen new candidates. Simulated experiments flow through metrics calculations just like physical tests, allowing us to navigate the space of potential new candidates to focus on those most promising while dropping others with fewer physical tests.

Manufacturing Teams Quantify how Product Mechanisms Lead to Production Variation

Root-Cause Production Variability

Understand the sensitivity of product performance to batch-to-batch variation in materials or control systems, by learning and simulating the root-cause mechanisms driving production variability.