Makersite
Cathleen Moynihan has extensive work experience in sales and business development, particularly in the technology industry. Cathleen has held various sales director roles in companies such as Domino Data Lab, Okera (now DataBricks), Element AI, SparkCognition, RapidMiner, Alteryx, Oracle, SAS Institute, Experian/Customer Insight Company, and IHS. In these roles, they have been responsible for driving sales and revenue growth, as well as managing major accounts and strategic sales opportunities. Cathleen has a strong background in selling data analytics, artificial intelligence, machine learning, and business intelligence solutions. Cathleen has a successful track record of working with Fortune 1000 companies and clients in various sectors, including government, insurance, manufacturing, technology, and finance.
Cathleen Moynihan has a Bachelor of Science Degree in Applied Business from NYU Stern School of Business, with a focus on Marketing Research, Statistics, and Computer Science. Prior to their college education, they attended The Mary Louis Academy for high school, where they studied Liberal Arts and Sciences, General Studies, and Humanities.
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Makersite
Makersite is a cloud-based product data management tool that helps companies manage product sustainability, cost, and compliance. Product life cycle management involves making design decisions based on multiple criteria including cost, compliance, sustainability, and risk. Unfortunately, the data and expertise required to make these decisions aresiloed. This protracts the process of innovation and increases its complexity. Today, the market solves this problem with vertical applications like PDM, ERP, CAD, EHS, SCM, etc. These mostly remain siloed due to the enormous costs of integration and keeping data synchronized. Therefore, analyses typically require exporting data to aggregation tools e.g. BI or excel before being used for analyses in specialist decision support applications. Results are typically delayed, some taking as much as 9 months, and therefore provide little support during the design process. Makersite provides results instantly and simultaneously across key product criteria.Makersite combines external and internal data sources to create a digital twin of a product in design. Artificial intelligence and its graph-based data model allow for ingesting, representing, and connecting heterogeneous data easily. Its native applications use algorithms to support analysis and decision-making based on multiple criteria simultaneously including should-costs, regulatory compliance, life cycle impacts (LCA), supply chain risk, etc. The API-first architecture allows for easy integrations into existing IT infrastructures thereby supporting systems and processes with richer, fresher, and more timely product data.This allows engineers to understand and improve their designs from the perspective of their regulatory compliance, environmental impact, supply risk, and cost of production, simultaneously. Companies can get results up to 40x faster than traditional methods while making their products better.