In high-stakes use cases, testing AI systems for reliability and safety is essential. And the stakes don’t get much higher than in the public sector! So, for our August meetup, we brought 90+ practitioners from the public and private sector together.
We invited a few best-in-class GenAI dev and testing practitioners from the public sector to share their experiences:
AIVF and IMDA released the insights and case studies from the Global AI Assurance Pilot on 29 May 2025 at the Asia Tech x Summit 2025.
Testing at scale across multiple use cases/teams by Benjamin Goh from National Group & GovTech Singapore
Ben shared about AI Guardian, a groundbreaking SaaS platform to enable GenAI testing across the public sector. Ben took us through the journey of implementing comprehensive AI testing and shared insights on creating standardised safety guardrails across teams through Litmus and Sentinel.
Embedding safety and reliability into GenAI for the legal sector by Eric Tan from IMDA Biztech
Eric spoke about how GPT Legal is transforming Singapore’s legal landscape. Eric revealed the intricate process of developing an LLM specifically for legal research, highlighting their partnership with Singapore Academy of Law and the implementation of robust safety measures throughout the development lifecycle.
Testing if your RAG application knows its limits by Jessica Foo & Shaun Khoo from GovTech Singapore
They shared exclusive insights into “KnowOrNot”, an innovative approach to detecting hallucinations in RAG applications, and how this open-source solution cleverly manipulates context to ensure AI remains grounded in reality – a game-changer for high-stakes applications.
Our speakers joined a collective, moderated Q&A session to take questions from the audience:
No posts found!
Your organisation’s background – Could you briefly share your organisation’s background (e.g. sector, goods/services offered, customers), AI solution(s) that has/have been developed/used/deployed in your organisation, and what it is used for (e.g. product recommendation, improving operation efficiency)?
Your AI Verify use case – Could you share the AI model and use case that was tested with AI Verify? Which version of AI Verify did you use?
Your experience with AI Verify – Could you share your journey in using AI Verify? For example, preparation work for the testing, any challenges faced, and how were they overcome? How did you find the testing process? Did it take long to complete the testing?
Your key learnings and insights – Could you share key learnings and insights from the testing process? For example, 2 to 3 key learnings from the testing process? Any actions you have taken after using AI Verify?