‍Greene Tweed Selects Uncountable as Their Preferred R&D Data Management Software Provider

‍Greene Tweed Selects Uncountable as Their Preferred R&D Data Management Software Provider

Greene Tweed, a market leader in high-performance specialty elastomers, has officially announced it will be implementing Uncountable as its cloud-based R&D platform provider. 
‍

SAN FRANCISCO, California, March 2023 – Greene Tweed, a premier provider of high-performance elastomers, thermoplastics, composites, and engineered components, has recently announced they’ve selected Uncountable as its R&D data management solutions provider. The company seeks to leverage Uncountable’s structured R&D data management software in conjunction with its cutting-edge predictive modeling capabilities to streamline its product development. Using Uncountable’s end-to-end platform, Greene Tweed will be able to build the framework they need to develop and use predictive modeling to their desired interest effectively.  

Bret Neese, the Technology Manager responsible for overseeing the Advanced Technology Group, led the overall initiative in evaluating various software solutions partners for his team. During this process, Neese’s primary focus was to find a solution that aligned with the company's scientific goals and could easily adapt across larger parts of the organization. Uncountable emerged as the ideal platform that offered the most potential to build a comprehensive data structure enabling accelerated innovation.

Uncountable is excited to partner with Greene Tweed and looks forward to extending the  collaboration and building a long-term partnership.

‍

For more information on Uncountable’s R&D solutions, visit www.uncountable.com. 

‍About Uncountable: Uncountable is an enterprise-class cloud platform for modern global R&D organizations. Our solution modernizes R&D workflows from siloed data sets and turns them into an integrated R&D knowledge base. With Uncountable, teams are empowered to unearth new learnings with built-in visualization tools and add predictive capabilities to their R&D toolset.

‍