BigGraph AI is a leader in digital and technology services, specializing in AI platforms underpinned by advanced graph theory, a key component of knowledge graph development. The company offers a comprehensive range of AI-driven solutions, including custom Large Language Models (LLMs) and Generative AI, tailored to meet the specific needs of diverse industries. With innovations like EulerRAG and domain-specific LLMs, BigGraph AI provides organizations in finance, healthcare, and technology with accurate, context-aware AI capabilities, enabling them to enhance decision making, streamline operations, and unlock new opportunities for growth. BigGraph innovates in technology, focused on exploring AI’s potential. Our goal is to unlock businesses’ potential and streamline operations with the most cutting-edge solutions. We offer tailored solutions for unique industries, working collaboratively with clients every step of the way. Join us as we push towards a brighter future with AI.
Reshape companies with Gen AI
Nageswar Keetha, President of BigGraph AI
Nag, with a Master’s in Computer Science from Columbia University and a dual degree in Mathematics and Computer Science from BITS Pilani, India, brings over 20 years of experience in technology industry. He has been a key figure in guiding Fortune 500 companies through transformative advancements in AI and is now leading BigGraph AI’s mission to redefine graph-based intelligence and leverage Generative AI through cutting-edge solutions.
Nag’s expertise covers Generative AI, Large Language Models (LLMs), and cloud-native computing on platforms like AWS, Azure, and Google Cloud. He has successfully led the transformation of legacy systems into AI-driven infrastructures, enhancing business intelligence and decision-making through AI copilots and advanced prompt engineering.
Under his leadership, BigGraph AI has introduced pioneering technologies such as EulerRAG (Eulerian Retrieval-Augmented Generation), which utilizes graph-based architectures and Eulerian principles to optimize data retrieval, scalability, accuracy, and contextual understanding in AI-driven decision-making.