The One About LLM Safety (ft. OCBC AI Lab)

​More information to come soon - keep a lookout! 👀

​More About the Sharings

• ​As generative AI becomes more adopted as a tool to uplift employee productivity, enterprises would require a high degree of accuracy when generating answers from referenced documents for a variety of tasks such as summarization or Q&A. Joven (Data Scientist, OCBC) will share more on Ragulator V3, an in-house lightweight tool that OCBC has developed to flag out of context LLM responses for RAG use cases. This project is currently presented in the 2025 EMNLP conference. (Technical Level: 200)

​More About the Speakers

• ​Joven Heng is a Data Scientist in OCBC's Risk and Customer Experience team, where he designs and deploys AI-driven solutions to mitigate risk and enhance customer journeys. With a bachelor's degree in business and a second major in computer science, he develops applications ranging from sentiment analysis of news articles for early risk signals to LLM-powered classification of customer feedback. His experience building agentic AI workflows and RAG models, particularly challenges with hallucination detection, sparked his interest in developing guardrails to improve the reliability of generative AI systems.

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