BasisAI: Accelerating AI Adoption with Google Cloud

技术

分析与建模 - 机器学习
网络安全和隐私 - 云安全

适用行业

设备与机械
运输

适用功能

产品研发
质量保证

用例

对话机器人
预测性维护

服务

云规划/设计/实施服务
培训

挑战

从聊天机器人到机器学习算法，人工智能 (AI) 推动着世界各地的数字化转型。据 Gartner 称，到 2024 年底，75% 的公司将部署真实世界的人工智能用例。然而，挑战在于确保人工智能系统公平且公正，特别是在金融和电信等行业，这些行业的决策可能会影响客户相信。 BasisAI 旨在通过提供 Bedrock 平台来应对这一挑战，帮助客户构建和管理负责任的人工智能应用程序。

关于客户

BasisAI 与各行业的大型企业合作，包括金融服务、保险、医疗保健和运输。他们的客户是希望释放人工智能的力量，同时确保人工智能系统的公平性和透明度的组织。这些组织了解构建负责任的人工智能应用程序的重要性，并希望利用人工智能来改善客户体验并获得数据洞察。

解决方案

BasisAI 在其专有操作系统 Bedrock 上提供从咨询到完全托管的机器学习操作 (MLOps) 的端到端人工智能服务。 Bedrock 是一种基于云的平台即服务 (PaaS)，使企业能够在现实环境中无偏见地部署负责任的人工智能。它提供了 MLOps 工具，使数据科学家和运营专业人员能够协作管理机器学习生产生命周期。 Bedrock 还提供用于训练、审查和部署 ML 系统的自动化工作流程，将 ML 系统的上市时间缩短高达 70%。

运营影响

The implementation of Google Cloud and the development of Bedrock have resulted in significant operational benefits for BasisAI. The company has been able to simplify the development experience and reduce the administrative burden, allowing data scientists to focus more on modeling. The use of Google Kubernetes Engine has enabled BasisAI to dynamically allocate resources to customer projects, saving costs on compute resources and reducing the time spent on infrastructure work. The company has also improved its security posture, identifying and resolving potential threats from misconfigurations and compliance violations. Furthermore, BasisAI has been able to provide its customers with full transparency on how each AI model works, promoting fairness and preventing unwanted biases. The company has also been able to test code before rolling into production, reducing the risk of issues in the deployment phase.

数量效益

Speeds up business impact for customers deploying ML models from prototype to production in minutes, not months
Reduces infrastructure burden by 25% with machine learning operations (MLOps) that enable data scientists to focus on modeling
Reduces the time-to-market of ML systems by up to 70%