Tung Hoang
I am a seasoned software engineer with an international footprint in Forbes 500 companies as well as VC-funded scale-ups in Europe and North America.
I have spent most of my career till now building resilient data and machine learning platforms. Most of them fail, some of them success but all of them give me lessons to learn from.
One of my success is being part of the team who built Komodo Health’s critical AI-fueled data analytic platform to actually save people. Our platform reduces the burden of disease research and reduce the cost of drug manufacturing and delivery.
Previously at Jellysmack, I worked on the core infrastructure team who scaled the data platform for a company who went from greenfield to unicorn startup in 2 years.
A part from that, I am a birds’ lover, an animal enthusiast, a day dreamer and a mediocre Judo player.
Session
Real-time data analytics is essential for powering modern applications like monitoring, personalization, search, and to some extend, RAG pipelines. However, building systems that can handle real-time ingestion, indexing, and retrieval at scale is no trivial task. This talk provides actionable insights into designing and maintaining such systems at scale using best practices.