Kavya V
Junior Forward Deployed Engineer at Tata Consultancy Services (TCS)
Madurai, India
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Kavya V is a Junior Forward Deployed Engineer at Tata Consultancy Services (TCS), working at the intersection of software engineering, cloud technologies, and artificial intelligence. A Google Cloud-certified professional holding PDE, PCDE, PMLE, and ACE certifications, she is passionate about exploring how emerging technologies can solve problems beyond the boundaries of conventional software.
Her technical interests span Generative AI, Large Language Models (LLMs), intelligent data retrieval, and computer vision. She has experience developing end-to-end applications and AI-driven systems, along with research experience in GNSS–PDR sensor fusion.
Kavya believes that the real challenge in AI is not making machines generate answers, but making those answers meaningful, reliable, and useful in the real world. She enjoys questioning common assumptions about technology, experimenting with practical implementations, and turning complex engineering concepts into accessible, engaging demonstrations.
Through her sessions, she aims to encourage developers to look beyond what AI can do and critically explore what it should do, where it can fail, and how we can engineer systems worthy of trust.
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From LLMs to Real-World AI: Building RAG-Powered Applications
This session demonstrates how to build real-world Generative AI applications using Retrieval-Augmented Generation (RAG). While Large Language Models are powerful, they often lack domain-specific knowledge and can produce hallucinated responses. This session addresses these limitations by integrating LLMs with external data sources through vector search.
Attendees will learn how to design and implement a RAG pipeline, including document ingestion, embedding generation, semantic retrieval, and response generation. A live demonstration will showcase a working AI application that answers questions based on custom documents, highlighting the difference between traditional LLM responses and RAG-based grounded outputs.
The session is designed to be practical (with LIVE DEMO), platform-agnostic, and applicable across cloud ecosystems such as Azure, Google Cloud, and OpenAI.
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