Overview

The Enterprise Compute Initiative (ECI) is a government programme launched in Budget 2025 to accelerate AI adoption in Singapore enterprises. The core idea is to provide enterprises access to cloud compute/AI infrastructure (credits, tools, platforms) plus consultancy services to develop proof-of-concept/MVP AI solutions with change management. It is designed to be short-term/catalytic to help jumpstart AI transformation in firms that are already somewhat prepared. The initiative is administered by Digital Industry Singapore (DISG) - a joint office drawing from EDB, IMDA, and EnterpriseSG.

Support Details

Support Rate

70% government support for consulting costs, company co-pays 30% (up to S$45,000 in many cases)

Cap

Up to S$555,000 total support envelope combining cloud credits and consultancy

Support Levels & Internal Caps by Pillar

Overall Support

Support Rate: Government supports part of consultancy costs in co-payment model, companies co-pay typically 30% of consulting cost

Grant Cap per New Market: Each participating enterprise can receive up to S$555,000 in total support (cloud + consulting)

Pillar	Max Grantable Amount
Cloud/Compute Credits & Tools	Large cloud credit allocations as part of CSP tailored packages
Consultancy/Implementation/Change Management	Maximum consulting cost supported capped at S$150,000
Microsoft Agentic AI Accelerator	Up to S$250,000 in Azure cloud credits + 70% consulting support up to S$105,000
AWS AI Springboard	Up to S$350,000 baseline cloud credits + up to S$105,000 consulting support

Note: These are maximum amounts within each pillar for a single new market. Each application must cover only one activity in a single overseas market.

Project Duration & Scope

Short-term catalytic programme with fairly tight timelines, often envisaged around 6 months for projects

Eligibility Criteria

Must be a company registered or incorporated in Singapore and physically present
Must have at least 10 staff based in Singapore
Senior management (CEO-level) sponsorship is expected
Should already have a tech/AI/data team of at least 2 staff (software engineers, AI/data roles)
Should have prior experience in building custom AI solution (proof-of-concept/pilot) or similar deployment
Must have accessible datasets to work with (data available)
Must have capacity (resources, funding, equity) to see through the project
Expected to deliver a Minimum Viable Product (MVP) plus change management outcome within programme period

Application Process

Partnership with CSP and consultant partner assignment - pick participating Cloud Service Provider (Microsoft, AWS)

CSP nominates/connects firm with consultant partners/SIs familiar with their platform

Proposal/use case submission with AI use cases, data readiness, roadmap, expected outcomes/MVP plan

Use case assessment for impact, readiness, technical feasibility

Onboarding and kickoff - receive cloud credits, access to tools, consultancy support on approval

Implementation/MVP building and testing - work with consultant partners to build MVP, iterate, test, integrate

Plan for operational embedding/scaling beyond MVP phase

Delivery and outcome/wrap-up - deliver MVP, validate change management/adoption, demonstrate business value

Performance/outcome reports may be required

Post-ECI support/next steps - further discussions with DISG/agencies about continuing AI/compute support

Processing Time

Application processing: 6-8 weeks for approval, Implementation: Around 6 months for project completion

Project Duration & Completion

Short-term catalytic programme with fairly tight timelines, often envisaged around 6 months for projects

Best Practices for a Successful Application

Ensure baseline readiness - ECI isn't for organisations starting from zero, need existing tech/data capability

Pick use cases strategically - aim for clear ROI or measurable value (cost savings, revenue uplift, automation)

Data readiness is critical - ensure data is clean, accessible, sufficiently large/relevant with proper permissions

Choose consultant partners with domain + AI experience - their guidance greatly affects success

Ensure leadership buy-in and alignment - projects with insufficient top-level support tend to stall

Plan for sustainability beyond MVP - think about scaling, operations/maintenance after ECI ends

Allocate resources internally - don't treat consultant as doing everything, internal team must be engaged

Be mindful of co-payment obligations and cost control - keep consultant cost within budget

Track progress and metrics carefully - define KPIs, monitor, course-correct

Apply early/quickly - since ECI is new and likely competitive, timely submission with polished use case helps

Leverage CSP packages and accelerators - Microsoft's Agentic AI Accelerator or AWS's AI Springboard provide bundled support

Sample Use Cases & Scenarios

Building custom AI solutions with clear ROI or measurable value (cost savings, revenue uplift, automation)

AI pilots with accessible, clean datasets and proper permissions/infrastructure

MVP development with change management and operational integration

Microsoft Agentic AI Accelerator: up to 300 Singapore enterprises with S$250,000 Azure credits

AWS AI Springboard: up to 300 firms with S$350,000 baseline cloud credits plus additional credits

Additional Information

Recent Developments and CSP Programmes: Microsoft Agentic AI Accelerator (part of ECI): • Participating companies receive up to S$250,000 in Azure cloud credits + AI tools/training • Government supports up to 70% of consulting costs, capped at S$105,000 per enterprise • Target: up to 300 Singapore enterprises AWS AI Springboard (part of ECI): • Eligible companies get up to S$350,000 baseline in cloud credits + additional cloud credits via other AWS programs • Government support of up to S$105,000 for consulting costs • Target: up to 300 firms Evaluation Criteria: Evaluation based on use case impact, organisation readiness, infrastructure readiness, and roadmap viability - not just meeting basic eligibility requirements. Short-term Catalytic Design: ECI is designed as short-term catalytic programme to help jumpstart AI transformation. Timeline typically around 6 months with focus on delivering MVP and change management outcomes. Key Support Components: • Cloud/compute credits and tools: Access to CSPs' cloud infrastructure, AI/compute resources, platform tools • Consultancy/implementation: Support for consultant partners to help plan AI roadmap, build MVP, do change management • Total support envelope: Combined support (cloud credits + consultancy) up to S$555,000 per enterprise • Co-payment model: Enterprises expected to co-pay portion of consultancy costs (typically 30%)