Makersite
Lorenzo Moneti's work experience includes positions as a Sales Development Representative at Makersite since May 2023, and at Glidian from January 2022 to January 2023. At Glidian, they played a role in revolutionizing the healthcare industry by developing a cloud-based prior authorization solution. Prior to this, they worked as a Customer Discovery Representative at VirtiMD from April 2021 to January 2022. Additionally, Lorenzo worked as a Sales Representative at Knewsales from October 2016 to August 2019, where they utilized direct sales techniques to persuade customers to sign up for credit cards, trained new employees, and was selected for a management position at a secondary location.
Lorenzo Moneti attended the University of Minnesota Duluth from 2017 to 2021. However, no specific degree or field of study information is available.
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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.