Machine Learning & AI Enterprise-level Secure Tool-Suite for Reliable Operations (MAESTRO)
Accelerate end-to-end AI/ML development and deployment with MAESTRO – a secure and compliant platform for WOG agencies to productionise their AI/ML use cases.
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MAESTRO is a centralised AI/MLOps platform that offers a comprehensive suite of tools and services for Singapore government agencies to productionise their AI/ML use cases within the Intranet.
Using MAESTRO, agencies can efficiently develop, deploy, and monitor their AI/ML models at scale within a secure and compliant environment, saving time and resources from not having to build an equivalent platform infrastructure.
To date, MAESTRO is utilized by more than 800 users across 40 agencies, including SSG, MOM, MCCY, HDB, Customs and many more. Cost avoidance of $2 million SGD per agency from not having to develop an equivalent system within the Intranet. More than 150 project teams to date, with a monthly average of 200k API calls from our model endpoints.
What is MAESTRO?
MAESTRO (Machine Learning & AI Enterprise-level Secure Tool-Suite for Reliable Operations) is a robust enterprise platform that empowers Whole-of-Government (WOG) agencies to seamlessly transition their AI/ML initiatives from Proof of Concept (POC) to production.
The platform provides a secure, trusted environment where agencies can rapidly prototype and validate AI/ML proof-of-concepts, design and implement automated workflows, and eventually deploy production-ready solutions.
In doing so, MAESTRO streamlines the entire AI/ML development lifecycle whilst ensuring compliance with government security standards and best practices.
Why use MAESTRO?
Government agencies in Singapore face significant challenges in productionising AI/ML use cases due to siloed development environments and labour-intensive processes that lack scalability and standardisation.
To move from experimentation to production, agencies require a secure, compliant, and cloud-based environment that supports the full AI/ML lifecycle—covering model training, deployment, and monitoring—as well as access to cutting-edge GenAI services and scalable compute resources.
However, building such an environment within the Intranet context is both complex and resource-intensive. Thus, a centralised platform like MAESTRO is essential to lower this barrier and help agencies accelerate the productionisation of AI/ML workloads.
Here are some of our platform features that help to enable this:
Security and Compliance
Hosted on Government on Commercial Cloud, MAESTRO is built in compliance with ICT & SS management standards, providing a secure and compliant environment within the government Intranet (GEN network) that is able to support agencies across various data classifications.
Infrastructure for AI/ML Lifecycle Management
MAESTRO caters the underlying infrastructure for end-to-end AI/ML lifecycle management, from model training to versioning, to deployment and ultimately monitoring.
Access to the latest Gen AI tools and services
MAESTRO provides users with cutting-edge generative AI technologies, including access to foundational Large Language Models (LLMs) from AWS Bedrock & Azure OpenAI via APIs, open-source models (e.g. Hugging Face) and even quantised models.
Scalable compute resources
WOG agencies and users can leverage MAESTRO’s scalable compute resources (e.g. CPUs, GPUs) to support their AI/ML development and production workloads.
Integrations with WOG Services and Agency Data Systems
MAESTRO is integrated with various WOG services, including data sources like DataHive & Data.gov as well as SHIP-HATS (e.g. Nexus, Gitlab). Agencies are also able to connect their own data systems with MAESTRO for seamless data exploitation and AI/ML development.
How to use MAESTRO?
Interested agencies can either visit our website at maestro.gov.sg (Intranet accessible only via GSIB/COMET) and click the “Register for Interest” button, or they can email our helpdesk at ag_helpdesk@tech.gov.sg.
To onboard MAESTRO, agencies will need their Chief Information Officer to sign a Letter of Undertaking (LOU) and nominate key user roles – including Agency Administrator, Project Lead, Data Scientist and/or ML Engineer.


