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Rohit

Rohit Sharma is a Senior Product Manager at Neysa.Ai, where he is focused on building the secure home for your AI. He is currently overseeing the development of three major products at Neysa- Velocis(Orchestration), Overwatch(Observability) and Aegis(Security). Prior to Neysa.Ai, he built mission-critical software for the armed forces at Hindustan Aeronautics Limited (HAL) and led key client engagements at Accenture, where he delivered transformative projects for multiple Fortune500 companies. His experience spans product development, AI-driven solutions, and strategic consulting, making him a leader in the intersection of technology and business. With a background in computer science and an MBA from Indian Institute of Management Bangalore (IIM Bangalore), Rohit has a unique blend of technical expertise and business acumen.

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Rohit

Scaling Open Source LLMs with a vLLM Inference Server

The article discusses the complexities of deploying large language models in production, emphasizing the importance of inference infrastructure, efficiency in request handling, and the role of vLLM inference servers in managing workloads effectively.

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Why NVIDIA H100 NVL Matters for Modern AI Systems

By 2026, open source AI has evolved significantly, with organizations now successfully implementing large models for various applications. The NVIDIA H100 NVL is crucial for maintaining consistent performance in inference-heavy workloads, addressing the growing demands for memory and stability. Managed GPU infrastructure supports continuous operations, reducing complexity and enhancing responsiveness in evolving AI systems.

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How Kubernetes Thinks and Acts: Inside the Control Plane and Worker Node Architecture

At scale, Kubernetes behaves less like a tool and more like a distributed operating system. Scheduling, recovery, and scaling all depend on how well the control plane and worker nodes interact. Decisions are centralized, execution is distributed, and reconciliation never stops. When these layers drift out of balance, reliability suffers.

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Enterprise AI: A Clear Guide for New AI Initiatives

Enterprise AI enables organisations to deploy and scale AI across operations, from customer experience to risk management. Success depends on connected infrastructure, governance, and workflows. Neysa’s AI Platform as a Service act as a ready workshop, letting teams assemble compute, storage, orchestration, and monitoring without bottlenecks, ensuring reliable, enterprise-wide AI adoption.

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AI Cloud Solution Explained: Why Security Must Be Built In, Not Added On

AI introduces new risks that legacy cloud architectures were never designed to handle. Without a secure AI Cloud Solution, organizations face exposure across data, models, access, and governance. This blog explores why traditional cloud security models fall short, and what secure AI infrastructure truly requires.

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What is AI Inference for Modern Enterprise Teams

AI inference is the moment a model meets real users. This blog follows a single prediction as it moves through an enterprise stack, showing how routing, hardware, scaling and monitoring shape latency, cost and overall product experience.

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