Future-proofing Singapore as an AI-first nation with Search AI

During the 2025 National Day Rally, Singapore’s Prime Minister Lawrence Wong announced a renewed commitment to empower Singaporean workers with AI and transform the nature of jobs as Singapore takes steps to adopt AI in business processes. He referenced an AI-powered orthopantomogram (OPG) scanner that flags dental conditions when analyzing X-rays, reducing the time taken for assessment from 15–20 minutes to 15–20 seconds.

This OPG scanner was just one of over 200 projects AI Singapore has delivered as part of its 100 Experiments program since 2018 — an effort to accelerate AI adoption by companies. Launched in May 2017, AI Singapore provides resources to companies developing AI products to perform use-inspired research, grow knowledge, create tools, and develop the talent to power Singapore’s AI efforts.

Elastic recently collaborated with AI Singapore to organize the Future-proof with AI workshop designed to cultivate a pipeline of AI builders and developers while showcasing practical, real-world applications. 

Elastic firmly supports Singapore’s national AI agenda and its developers. We believe that the AI push isn’t just about the technology; it’s also about the skills of the people driving it. Developers are a company’s superpower. And with the right AI skills, they can build innovative applications to showcase their expertise, create new opportunities for themselves and their organizations, and take their teams further to differentiate themselves from the competition.

The initiative was kick-started by Tess Ang, account manager at Elastic. Held in August at AI Singapore’s office, the event attracted professionals from various industries, including public sector, financial services, semiconductor, aerospace, travel, and ecommerce.

The workshop began with Meldrick Wee, lead AI engineer at AI Singapore, explaining large language model (LLM) prompt engineering techniques from starting simple and being specific to in-depth techniques, such as query decomposition, zero-shot, few-shot, and chain-of-thought prompting. 

This provided a preview of AI Singapore’s LLM Application Developer Programme (LADP) designed to help organizations accelerate their adoption of LLMs by equipping participants with fundamental knowledge and skills in prompt engineering, ultimately enabling them to build LLM-powered applications with guidance from AI engineers.

Participants learned about Elastic’s Search AI capabilities from solution architects Han Xiang Choong and Zing Zai Loo, focusing on industry use cases of operationally valuable generative AI applications. Effective AI applications use search techniques like retrieval augmented generation (RAG) to improve search relevance by adding contextual information from private or proprietary data sources that enrich LLM outputs without retraining them. 

Building effective AI applications starts with having the right data at the right time. As the volume of data in organizations grows, it becomes increasingly difficult for customers and employees to find answers to their questions within that data using conventional methods. Advanced search capabilities like semantic search are critical for data retrieval at scale, enabling AI use cases across industries.

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