Normalized claim
Public sector organizations adopted: 20 organizations increase
Within 9 months of launch, MAESTRO was adopted by 20 public sector organizations
GovTech collaborates with AWS Generative AI Innovation Center to scale generative AI adoption across public sector organizations
Use case typeMLOps platformUpdated Jul 15, 2026
GovTech built MAESTRO, an end-to-end AI/ML development platform to scale generative AI adoption across Singapore government agencies. The platform helps agencies create cost-efficient generative AI tools and production-ready use cases with a no-code ML interface.
- Organization
- Government Technology Agency
- Industry
- Public Sector
- Location
- Singapore
- Published
- July 2026
Reported outcomes
10,000,000 job postings
job postings processedQuality & accuracy
20 organizationspublic sector organizations adopted1,000,000 documentsdocuments processed−50%sensemaking time reduction2,000 hourswork hours saved+75%cost performance improvement
Strategic outcomes
Cost efficiencyAccelerated generative AI adoption across agenciesCost efficiencyEnabled production-ready generative AI use cases
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Documents processed: 1,000,000 documents increase
Within 3 months, MOM used the tool to process over 1 million documents
Normalized claim
Sensemaking time reduction: 50% decrease
reduce sensemaking time by 50 percent
Normalized claim
Work hours saved: 2,000 hours increase
save over 2,000 work hours
Normalized claim
Job postings processed: 10,000,000 job postings increase
the SSOC Autocoder had processed 10 million job postings with 92 percent accuracy
Normalized claim
Cost performance improvement: 75% increase
MAESTRO improved cost performance for generative AI workloads by up to 75 percent
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Government Technology Agency, Ministry of Manpower
- Provider
- AWS
- Maturity
- Production
- Linked source
- AWS Solutions Case Study
Overcome the high cost and operational complexity of running LLM-based generative AI at government scale
Customer identity supportedSource describes one deploymentMaturity supported
Primary read
Use case focus
Showing 2 of 2
- 1MLOps platform
- 2Workflow automation
- Overcome the high cost and operational complexity of running LLM-based generative AI at government scale.
- Help public sector organizations rapidly create and deploy production-ready generative AI tools.
- Built MAESTRO with the AWS Generative AI Innovation Center as an end-to-end AI/ML development solution for government agencies.
- The platform uses Amazon SageMaker Studio, Amazon SageMaker Canvas, and Amazon SageMaker JumpStart to simplify building, training, deploying, and managing ML models.
- It incorporates ready-made foundation models and quantization techniques to improve cost performance and enable cost-efficient AI/ML operations.
- Within 9 months of launch, MAESTRO was adopted by 20 public sector organizations.
- The platform reached more than 45 project teams and over 300 data scientists and ML engineers.
- MOM processed over 1 million documents in 3 months, improved insights extraction by 60%, reduced sensemaking time by 50%, and saved over 2,000 work hours.
- The SSOC Autocoder processed 10 million job postings with 92% accuracy.
- MAESTRO improved cost performance for generative AI workloads by up to 75%.
Architecture
GovTech built MAESTRO as an end-to-end AI/ML development platform using Amazon SageMaker Studio, Amazon SageMaker Canvas, and Amazon SageMaker JumpStart. The platform supports no-code ML workflows, ready-made foundation models, and quantization techniques to help Singapore public sector organizations build and deploy generative AI solutions at scale.
Sources & evidence1
Evidence: Medium65/100Evidence strength
- Customer explicitly identified
- Deployment status explicitly supported
- Primary source available
- Quantified outcome available
- Technical implementation details available
Type: Customer StoryPublished: Jul 15, 2026Publisher: AWSEvidence: PrimaryConfidence: High
AI-generated summary. Verify important details with the linked sources before relying on this case.
Explore related AI use cases
Customer evidence
Provider evidence
Browse the catalog
Was this useful?
Community
Comments
No published comments yet.