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Joseph
Thangraj
Lead Data Scientist, GenAI
Sanofi
Joseph Thangraj, Ph.D. is Lead Data Scientist at Sanofi, specialising in generative AI and machine learning solutions across healthcare and life sciences. He has led cross functional teams to deliver end to end AI products spanning GenAI document generation, time series forecasting, NLP, and optimisation systems, with a focus on driving measurable business and clinical impact. With a PhD in Computational Geophysics and an IIT background, Joseph combines strong theoretical grounding with hands on engineering expertise. His work includes deploying production grade AI systems on AWS, building scalable ETL pipelines, and applying deep learning to complex healthcare and industrial problems. At the summit, he brings practical insight into building trusted, production ready GenAI systems in regulated environments.
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29 October 2026 12:30 - 13:00
Panel | From GenAI to autonomous workflows: how teams are evolving their AI systems
A generative output that a person reads is easy to forgive. One that feeds the next step in a workflow is not. Most generative stacks were designed for one-off results: a prompt, a retrieval step, and an answer someone checks. Once those outputs start feeding other steps and triggering real actions, the prompting, retrieval and evaluation choices that worked in isolation start to break. So what has to change in the stack before it can carry real work? This session brings together practitioners who are rebuilding their generative stack around workflows. They'll cover where their original design stopped holding up and what they changed. Through real examples and open disagreement, the panel will get into how prompting, retrieval and evaluation shift when outputs become dependencies, and how they decide when a system is ready to act without a person checking every step. Key takeaways: → Where stacks built for one-off results break once outputs feed other steps → How to design prompting, retrieval and evaluation for outputs that trigger actions → What to put in place before letting a system act on its own The questions still line up with the new takeaways: