MLDS speaker · 2026
Paulami Das
Vice President, Data Science & AI PlatformPayU
About Paulami Das
At PayU, Paulami has built and scaled high-performing data science and engineering teams, leading a 45-member organization responsible for developing enterprise-grade AI products and scaling ML-as-a-Service platforms. She oversees AI platform strategy, data security, compliance, and operational excellence, enabling accelerated ML product deployment while ensuring regulatory adherence. Prior to PayU, she served as Head of Data Science CoE / Principal Data Scientist at Brillio, where she led AI Labs and built cutting-edge AI/ML accelerators across Natural Language Processing, Computer Vision, and Augmented Insights. She also held leadership roles at Cytel, driving business growth, scaling technical teams, and contributing to strategic organizational expansion. In addition to her corporate leadership, Paulami serves as a Board Member and Technology Advisor at Sampark, contributing to technology-led impact initiatives. A recognized AI thought leader, she is frequently invited to speak at industry forums on data strategy, AI platforms, emerging technologies, and the future of enterprise AI. Her work sits at the intersection of deep technical expertise, platform thinking, and business transformation.
1 edition on the MLDS stage · 1 session on record

Talks at MLDS
Sessions from the MLDS agendas, newest first.
MLDS 2026
Bengaluru
26–27 Mar 2026Mar 26, 2026 · 16:05–16:25 · Hall 3 · Bengaluru
Tech TalksExpert-First: Anchoring Agents in Subject Matter Knowledge
As AI agents become more prevalent across industries, ensuring they operate with the depth and accuracy of true subject matter expertise is becoming increasingly important. An expert-first approach focuses on anchoring AI agents in structured domain knowledge, expert insights, and reliable information sources rather than relying solely on generalized model outputs. This session will explore why grounding AI agents in subject matter knowledge is essential for building trustworthy and effective AI systems. It will discuss the role of expert input, curated knowledge sources, and contextual understanding in enabling agents to deliver more accurate, relevant, and meaningful outcomes. The session will also highlight how organizations can design AI solutions that combine the power of large language models with domain expertise to create more reliable and impactful AI-driven experiences.
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