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Ashwin
Naidu
Lead Data Scientist
Deutsche Bank
Ashwin Naidu is a Lead Data Scientist at Deutsche Bank with over a decade of experience applying AI to solve complex challenges across financial services, healthcare, and energy. He specializes in large language models, retrieval-augmented generation (RAG), and agentic AI systems, with expertise spanning machine learning, NLP, and scalable AI architectures. Passionate about turning research into production-ready solutions, Ashwin combines deep technical knowledge with leadership experience to deliver responsible, high-impact AI innovation.
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19 August 2026 09:00 - 09:30
The production gap: What actually changes when agentic AI moves from pilot to live financial workflows
Getting an agentic system working in a notebook is one problem. Keeping it working in a production financial environment, where data is inconsistent, latency matters, and a wrong output carries real consequences, is a different one entirely. This session unpacks what that transition actually looks like: the architectural decisions that don't survive contact with real environments, the organisational friction nobody plans for, and what separates teams shipping in production from teams still cycling through proofs of concept. Key takeaways: - Why architecture choices that work in a POC often break under production load and latency constraints - What data inconsistency actually costs an agentic pipeline once it's live - The organisational friction that slows teams down between pilot and go-live - What separates teams that get agentic systems into production from teams stuck in POC cycles If you are moving an agentic system from proof of concept into live financial workflows, this session is for you.