Provectus > 实例探究 > 通过云原生 MLOps 平台加速 AI/ML 的采用

通过云原生 MLOps 平台加速 AI/ML 的采用

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技术
  • 分析与建模 - 机器学习
  • 平台即服务 (PaaS) - 应用开发平台
适用行业
  • 水泥
  • 药品
适用功能
  • 维护
  • 产品研发
用例
  • 施工管理
  • 基础设施检查
服务
  • 数据科学服务
  • 培训
关于客户
该客户是消费者健康、医疗器械和制药领域的全球医疗保健领导者。他们在全球雇用了超过 130,000 名员工,并致力于创新和改善全球健康。
挑战
我们的客户是一家全球医疗保健领导者,希望在其组织内加速和扩大 AI/ML 的采用。他们需要一个现代化的 MLOps 平台来简化 AI/ML 应用程序的开发和部署。
解决方案
Provectus 在 AWS 上实施了云原生 MLOps 平台,为客户的解决方案提供了基础。他们还为未来的项目准备了 AI/ML 项目模板,并为入职数据科学家和 ML 工程师提供了全面的文档。
运营影响
  • With assistance from Provectus, the client was able to start using their new MLOps platform in a matter of months, to optimize and streamline the operationalization of AI/ML projects. The MLOps platform and accompanying templates offered the client’s ML engineering team a convenient foundation for initiating the productionalization of new AI/ML projects and onboarding existing AI initiatives. The introduction of these innovations significantly accelerated the time-to-market value of the client’s AI/ML projects. The comprehensive documentation of the MLOps platform, seed code implementation and deployment, as well as AI/ML project onboarding guides prepared by Provectus, significantly reduced the entry barrier to understanding existing solutions and the development of new AI/ML solutions and projects. These deliverables from Provectus have empowered the client to develop and deploy future AI/ML applications more rapidly, efficiently, and at a larger scale. The delivered solution facilitates data-driven decision-making, leading to greater business success and a competitive advantage in the market.

数量效益
  • The amount of manual work required to set up infrastructure for AI/ML projects was significantly reduced or nearly eliminated.

  • The costs of Proof of Concept development were reduced by minimizing the need for additional personnel such as software and DevOps engineers.

  • The infrastructure approval process for AI/ML project development was expedited due to the standardization provided by the MLOps platform.

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