Saurabh Mishra is a technology leader focused on delivering value through enterprise AI solutions. He leads as the Director of Product, AI and Industrial Applications at SAS. He has over 20 years of experience in enterprise AI, SaaS and data platforms. Prior to joining SAS, Saurabh spent a number of years in the Industry in product development, business analysis and consulting roles. Saurabh holds a Master of Science degree in Operations Research from Georgia Tech and a Bachelors of Technology degree in Computer Science & Engineering from Indian Institute of Technology.
Getting an AI agent to complete a task is a meaningful milestone. But for enterprise AI agents, “it works” is only the beginning. The bigger question is whether the agent can perform reliably, efficiently and consistently enough to move into production. That means looking beyond a successful output. Could the
Many conversations about AI agents focus on models and frameworks. But when organizations attempt to deploy agents in real operational environments, a different challenge quickly emerges. How agents reliably and securely access enterprise data. Without reliable access to relevant data, AI agents struggle to support operational decisions. Whether diagnosing equipment
Since the idea of an “IoT analytical lifecycle,” may be understood in many different ways, let’s start with a definition. Performing analytics at the data center and the cloud is well established practice, and is still quite relevant. With growing numbers of connected devices and availability of computing capabilities at
