Decision Models for Guardrails: Exploring Jev and Kev for Moderation
A closer look at the new paradigm of frontier models, and how we explored Jev and adapted its open-source interpretation - Kev, for Singapore-context moderation.
Responsible AI
A collection of 16 posts
Behind VEILED Expressions: A Singapore-context benchmark for mental-health AI evaluation
We built VEILED-SH to evaluate indirect self-harm/suicide language in the Singapore context, shaped by local language, privacy safeguards and practitioner insight.
Building a Smart and Safe Whole-of-Government Chatbot for Singaporeans
How we build custom policy guardrails and balance safety with helpfulness for chat.gov.sg
Guardrails in the Wild: Closing the Retraining Loop for LionGuard 2
Operationalising MLOps with production feedback to continuously evaluate, retrain, and improve our guardrails.
My 6 Months Interning Responsibly at AI Practice
Tell us about yourself- what did you expect from this internship?
I’m Rohan, a penultimate year Business Analytics student at the National University of Singapore (NUS) who spent the first half of 2026 as an applied AI Data Scientist Intern at GovTech’s Responsible AI team.
Going in, I
Building an automated Evals workflow that works (and open-sourcing it)
How we built Kaleidoscope: A structured workflow for realistic, scalable, and human-aligned contextual AI evaluations.
Yes, you’re absolutely right… Right? A mini survey on LLM sycophancy
Ever spoken to an AI and felt like it was responding with insincere praise?
Benchmarking GPT-5 & GPT-OSS: A Responsible AI Approach
Evaluating dimensions often overlooked by traditional benchmarks.
Introducing LionGuard 2: Multilingual LLM Guardrail for Singapore
We improved its coverage and robustness.
RabakBench: Multilingual AI Safety Evaluation Made Local
Global safety guardrails are often blind to local dialects and sensitivities.
Does your LLM know when to say “I don’t know”?
Refusal by a model to answer may sometimes be more valuable.
Fine-Tuning Language Models for Long-Context Data: Automated Stance Analysis of Citizen Discussions
Addressing technical challenges of processing high-volume public feedback for policy-making
Securing Guardrails with Automated Red Teaming
Manual testing is no longer scalable.
(Part 2) LLM Safety Alignment for the Singapore Context using Supervised Fine-tuning and RLHF-based Methods
Safety must be "baked in".
(Part 1) LLM Safety Alignment for the Singapore Context using Supervised Fine-tuning and RLHF-based Methods
The process of "teaching" models to be safe
Eliciting Toxic Singlish from r1
A red-teaming exercise that proves even "reasoning" models can be coaxed.