Ranjani Mani

Ranjani Mani

Director and Country Head, Generative AI, India and South Asia

Microsoft

Ranjani Mani is a technology enthusiast and avid reader who is committed to self-improvement. She believes that women can achieve great success in the tech industry and is dedicated to helping them break through the glass ceiling. With over 15 years of experience in data science, product management, consulting, and customer experience analytics, Ranjani has worked with some of the biggest names in tech, including Dell, Oracle, VMWare, Atlassian and now Microsoft.

Ranjani’s academic achievements are impressive, having graduated top of her class with a Bachelor’s degree in Engineering, Electronics, and Communication. She then went on to earn a silver medal in her Masters in Business Administration from MICA, Ahmedabad.

Ranjani’s values are centered around taking ownership, putting people first, starting with why, acting fast, failing quickly, iterating, and playing fair. She is passionate about solving user problems through building analytics capabilities, product strategy, and leadership. Currently, Ranjani leads a global team of Analytics Managers, Data Scientists, and Business Analysts at Microsoft, where she is responsible for building analytics capabilities and scaling teams.

Ranjani writes extensively on topics such as technology, books, leadership, strategy, and analytics. She hopes to inspire and empower women to overcome the broken rung and scale into tech leadership roles to live up to their full potential.

Voice is fast becoming the most natural and intuitive way for humans to interact with machines. With the rise of AI-powered voice agents, we're entering a new era where conversations, not clicks, drive digital experiences. This session explores how advancements in generative AI, speech recognition, and real-time synthesis are reshaping human-computer interaction. Discover the latest trends, architectures, and real-world use cases where AI voice agents are revolutionizing industries—from customer service to healthcare and beyond. Join us to understand the future possibilities and what it takes to build intelligent, responsive, and human-like voice interfaces.

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Managing and scaling ML workloads have never been a bigger challenge in the past. Data scientists are looking for collaboration, building, training, and re-iterating thousands of AI experiments. On the flip side ML engineers are looking for distributed training, artifact management, and automated deployment for high performance

Read More

Managing and scaling ML workloads have never been a bigger challenge in the past. Data scientists are looking for collaboration, building, training, and re-iterating thousands of AI experiments. On the flip side ML engineers are looking for distributed training, artifact management, and automated deployment for high performance

Read More
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