Foster an organizational culture that prevents rework of analyses that your team has previously done and saved as siloed data. Capture and index high volumes of historical data and analyses in a unified and centralized knowledge management system. Share your knowledge across your teams and reap the benefits of collective intelligence.
Our products and services are designed to make statistical methods and analysis easier for engineers, scientists and other analysts to work with on a daily basis and to boost productivity and knowledge transfer across your organization.
A common problem that companies face is losing their investment in knowledge soon after their staff generates that knowledge. Once a problem is solved, the improvement is realized or the R&D project has been completed, the associated knowledge work, including the data, analysis and resulting predictive models, become lost or inaccessible to others.
These real-world problems are why we pioneered our analytical products. These products maintain your investment in the core work of engineers, scientists and other analysts. Staff can work independently and in collaboration with their colleagues to preserve institutional knowledge, even when staff are absent or no longer with the company. Knowledge work is identifiable, searchable, retrievable, reusable, and shared by everyone in the organization who depends on it.
Outpace competitors respond to supply chain disruptions. Accelerate your research and development shorten your experimentation cycles. SashLAB is a virtual lab application that enables engineers scientists and researchers to perform experiments virtually to fully vet designs of compounds and formulations effectively in minutes.
Develop better products. Improve existing processes. Extract more experimental insights. Build more accurate predictive models. And do it all in less time—at a lower cost with Self-Validating Ensemble Modeling. SVEM helps you build predictive models quickly and cost effectively by combining the power of machine learning and design of experiments.