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Analytics.gov – Enabling AI/ML Operations for Whole-of-Government (WOG)

AG is a secure government platform for developing, deploying, and monitoring AI/ML models.
Faster AI/ML project development with pre-built templates (Python & R compatible).
Ensures governance and compliance with data security standards.
Enables collaboration and reuse of AI/ML components across government projects.
Used by over 350 users across 20+ public agencies (e.g. HDB, MOM, SkillsFuture).
Analytics.gov (AG) is a secure platform for government agencies to develop, deploy, and monitor their AI/ML models at scale. It is hosted on GCC 2.0 and provides tools and services for more than 350 users across 20 public agencies. Agencies like Housing Development Board, Ministry of Manpower, and SkillsFuture Singapore are using the platform to efficiently develop, test, and deploy AI/ML models.
As a readily available AI/ML Ops environment, any agency can work on their data projects right away without the need for them to expend additional time and effort to develop equivalent systems on their own.
Why use AG?
Here are 4 main reasons why you should use AG:
Automation
Teams can use pre-defined configurations and templates (both Python and R compatible) to accelerate their AI/ML projects.
Scalability
The platform is built to seamlessly handle increasing adoption numbers amidst growing AI/ML workloads.
Governance and compliance
AG complies with ICT and SS management standards and allows team admins to track workflow activities for transparency and accountability.
WOG collaboration
The platform encourages collaboration and reuse of software components across government projects.
The standardised workflows in place will help data science teams streamline their processes to ensure quick and efficient model deployment.— Jeffrey Chai, Product Manager
This will empower data teams both within and across government agencies to collaborate and accelerate machine learning innovation real-time co-working capabilities.— Jeffrey Chai, Product Manager
What's the latest on AG?
AG introduced MLOps capabilities with Amazon SageMaker Studio, allowing agencies to train, deploy, and monitor models automatically at scale. Its standardised workflows boost the productivity of data science teams while maintaining model performance and quality in production.
AG also introduces Amazon SageMaker Jumpstart, giving users access to foundation models and pre-built algorithms for common ML tasks, such as data classification and sentiment analysis. AG also supports users in hosting quantised models.
In March 2024, AG piloted exclusive user access to Amazon Bedrock in the AWS Singapore (SG) region, enabling users to experiment with and evaluate models via APIs.
As a central WOG platform, AG will continue to explore similar MLOps services from other cloud service providers.