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Integrating the Custom Solutions of a Technology Powerhouse
技术
- 平台即服务 (PaaS) - 数据管理平台
适用行业
- 生命科学
适用功能
- 产品研发
- 质量保证
用例
- 预测性维护
服务
- 软件设计与工程服务
- 系统集成
挑战
Zymergen, an industrial biotechnology company, was facing challenges with its custom software systems. The company had many siloed pieces of custom software, making it difficult for scientists to enter and extract data. The strain optimization and fermentation & production teams couldn’t share complete experimental context due to the disparate systems. Moreover, Zymergen’s systems couldn’t scale with their rapidly growing company. The company needed a solution that could integrate their custom tools and provide a central platform for data entry and extraction.
关于客户
Zymergen is an industrial biotechnology company that engineers microbes to produce high-value commercial molecules. The company employs many custom software systems and algorithms that allow their scientists to push the boundaries of strain engineering. Zymergen's work involves a lot of data entry and extraction, and the company was using multiple siloed pieces of custom software for this purpose. The company's strain optimization and fermentation & production teams were unable to share complete experimental context due to the disparate systems. Furthermore, Zymergen's systems were not scalable enough to keep up with the company's rapid growth.
解决方案
Zymergen adopted Benchling as a central platform to unite their custom tools. Proprietary algorithms, instruments, and niche software all integrated into Benchling. The company was able to integrate custom sequence analysis algorithms with Benchling, eliminating data import/export. By integrating automated data capture across plate groups, Zymergen was able to populate notebook entries with data in real-time. With centralized functional data, analysis, and records, Zymergen was able to generate decision-quality results at a competitive speed. Benchling's permissions features intelligently restricted data access, allowing more of their clients to share classified data.
运营影响
数量效益
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