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Anthropic opened a Singapore office on 14 October 2026 and signed a Memorandum of Understanding (MOU) with Singapore’s Ministry of Digital Development and Information (MDDI). The agreement creates a framework for cooperation on AI safety, security, model evaluation, adoption research, workforce skills and responsible use across government and industry.
What Anthropic and Singapore agreed to do
The MOU was signed by Anthropic co-founder Ben Mann and MDDI Permanent Secretary Kai Fong Chng. Minister Josephine Teo and Anthropic APAC policy head Michael Sellitto witnessed the signing.
Rather than announcing a single software purchase or deployment, the MOU sets out several areas for joint work:
| Area | Planned cooperation |
|---|---|
| Safety and security | Exchange expertise on AI safety, security practices and incident response. |
| Model evaluation | Technical exchanges on model evaluation and testing standards. |
| Adoption research | Research into how AI is adopted and its effects on organizations and society. |
| Responsible deployment | Support responsible adoption in both public-sector and private-sector settings. |
| Skills and capability | Develop AI skills, strengthen public-officer capability and support small and medium-sized businesses. |
| Policy and research | Share research and policy expertise between the parties. |
The announcement does not specify a budget, a procurement commitment, an exclusive-supplier arrangement, a delivery timetable or a new Singapore-specific model. Those details should not be inferred from the MOU.
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Why Anthropic is establishing an office in Singapore
Anthropic says Singapore ranks second among 121 countries for Claude.ai use relative to population. Its usage is nearly six times what the country’s population alone would predict, according to Anthropic’s 2026 figures. That makes Singapore an unusually concentrated market for the company’s consumer and developer products.
The office is intended to give customers, developers and policymakers a local point of contact while supporting a growing Singapore-based team. Anthropic described it as the company’s fifth office in Asia-Pacific. A September report by CNA said the company planned to hire across several teams, indicating that the location is more than a small representative presence.
Dale Finlay, Anthropic’s general manager of ASEAN, said: “We’re committed to Singapore for the long term.” The company’s decision also places it close to a government that has made model testing and responsible-AI policy a stated priority.
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How Singapore organizations are using Claude
The strongest evidence of local adoption comes from named deployments in government, finance, technology, transport and commerce. Anthropic supplied the following examples:
| Organization | Use of Claude | Reported scale or result |
|---|---|---|
| GovTech Singapore | Claude Code for modernizing government systems and accelerating software delivery. | More than 1,500 engineers and technical staff have adopted it. |
| DBS | Software development and day-to-day productivity within the bank’s security and governance framework. | No public productivity figure was given. |
| GIC | Rollout across investment and corporate-services teams. | No public user count was given. |
| Grab | BriX sales assistant powered by Claude. | Anthropic says it saves sales teams approximately 40,000 hours every quarter and helps surface new opportunities. |
| Sea | Customer-service responses for Shopee and employee coding. | No public usage figure was given. |
| Supabase | Building software with Claude Code. | No public usage figure was given. |
The 40,000-hour figure for Grab is an Anthropic-reported estimate, not an independently audited benchmark. Similarly, the GovTech figure describes adoption by engineers and technical staff; it does not mean every Singapore government service has been automated.
What the MOU could change for AI safety and testing
The safety portion is significant because it connects a model provider with a national ministry on practical evaluation work, rather than limiting cooperation to general policy statements. Technical exchanges could cover how models are tested before release, how performance is monitored after deployment and how organizations respond when a system behaves unexpectedly.
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Model-evaluation and testing standards are especially important for public-sector systems, where a failure can affect many people or involve sensitive information. Incident-response cooperation could help clarify escalation routes, evidence collection and communication when a deployed model produces harmful or unreliable output. The MOU also links safety work with skills training, so public officers and smaller businesses can develop the ability to assess systems instead of treating model outputs as automatically trustworthy.
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Kai Fong Chng said: “Singapore has been a leader in responsible AI, with a long track record of investment in model testing and evaluation.” That statement explains the policy fit, but the announcement does not yet publish a new test protocol, pass/fail threshold, audit schedule or incident-reporting requirement. The concrete standards and projects will need to be defined through subsequent work.
In-region inference for regulated-sector deployments
Anthropic says regulated-sector organizations can run Claude with in-region inference on Amazon Bedrock. Processing inference within the relevant region can be important for organizations that must meet data-governance, residency or sector-specific handling requirements.
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In-region inference is a deployment option, not a blanket guarantee that every workload complies with a particular law or policy. Organizations still need to check the applicable data classification, retention, access-control, logging and contractual requirements. The announcement does not state eligibility, pricing, service-level terms or which Singapore workloads are currently supported.
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Singapore government agencies
Agencies gain a local channel for technical discussions, training and evaluation practices. GovTech’s reported Claude Code adoption suggests that software modernization is already an active use case, while the MOU could extend attention to testing and incident response.
Financial and other regulated companies
DBS and GIC show that financial institutions are testing Claude inside formal security and governance arrangements. In-region inference through Amazon Bedrock may be relevant when data-location controls are part of an approval process, but each organization must perform its own compliance review.
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Small and medium-sized businesses
The MOU explicitly includes SME adoption and AI skills. That could lower the expertise barrier for companies that want to use models but lack dedicated evaluation or policy teams. No grant, subsidy or rollout schedule has been announced.
Developers and researchers
A local office and planned research exchanges provide a Singapore-based contact for developers, universities and technical specialists. The agreement’s emphasis on evaluation may also encourage more locally relevant testing and sharing of safety findings.
What to watch next
- Specific model-evaluation methods or testing standards produced through the technical exchanges.
- Whether Singapore agencies publish guidance for incident reporting and response involving generative-AI systems.
- New training or capability programs for public officers and SMEs.
- Additional hiring and customer-support activity from Anthropic’s Singapore team.
- Details on which regulated workloads can use in-region inference, under what terms and with what data controls.
For now, the announcement establishes a cooperation framework and confirms substantial local interest in Claude. Its long-term effect will depend on the standards, training and deployment practices that follow the signing.
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