Granica
Rahul Ponnala is an experienced professional with a diverse range of roles in the technology industry. Rahul is currently serving as the CEO and Co-Founder of Granica, a company focused on AI research and software tools. Prior to this, Rahul was the Director of Solutions & Integrations Engineering at Pure Storage. Rahul also held positions as the Head of Solutions Engineering at GyanSys Inc., Senior Solutions Architect at Flexware Innovation, and Software Engineer at Apparatus. Rahul started their career as a Software Engineer at ITT Educational Services, Inc. In addition to their professional roles, Rahul is an angel investor and a board member of the FinOps Foundation. Rahul is also a Fellow at the British Computer Society.
Rahul Ponnala has a Master of Science degree in Mathematics and Computer Science from Indiana State University. Rahul also holds a Bachelor of Technology degree in Electronics and Communications Engineering from Jawaharlal Nehru Technological University.
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Granica
Granica is an AI research and systems company helping enterprises leverage AI efficiently and safely. Our mission is to make AI 10,000x better. We believe data is the first-mile problem to solve in this mission. Our first system is a novel training data platform for enterprise AI that unlocks efficiency and privacy through our flagship services tailored for Generative and Traditional AI: Granica Crunch is a family of advanced data compression/reduction models which enable AI/ML teams to add and use more data to improve their ML accuracy and performance while controlling their infrastructure costs. Crunch delivers deep cost efficiencies for data at any scale, at rest and in use. Granica Screen is an advanced data privacy-enhancing service that unlocks even more data for AI/ML teams to safely improve model performance. It guarantees state-of-the-art privacy at scale, enabling Private LLMs and Privacy-preserving AI. Granica Chronicle is a deep data visibility service for disparate AI data stores. Enabling unification, collaboration and insights into data usage for AI and ML. Our research is deeply rooted in information science, machine intelligence, computer vision, natural language, and distributed systems, with a special emphasis on elevating the efficiency and safety of AI systems through fundamental and innovative research. We're backed by remarkable institutional investors in AI, Data, and Cloud; and several industry luminaries in business and technology.