Skip to main content

    Author

    Vinod Kumar

    Chief Executive Officer, ZigmaNeuralVinod Kumar leads ZigmaNeural, advising enterprise leaders on AI strategy, connected products and technology investment decisions.

    Topics Vinod writes about

    • Enterprise AI
    • RAG
    • AI governance
    • AI Strategy
    • MLOps
    • LLM costs
    • AI budgeting
    • token pricing
    • prompt caching
    • batch API
    • AI strategy
    • EU AI Act

    Articles by Vinod Kumar

    Insights

    What an LLM Feature Really Costs to Run for a Year

    Three worked examples with real per-token prices show what a chatbot, a document Q&A tool and a batch job cost per month and per year.

    October 26, 2026

    Insights

    EU AI Act: What Indian AI Vendors Serving EU Clients Must Do

    If your AI system or its output is used in the EU, the AI Act can apply to you. Here is what changed in 2026 and what Indian vendors should do now.

    October 26, 2026

    Insights

    India's DPDP Act and AI Projects: A Practical Checklist

    What India's DPDP Act and Rules mean for RAG, chatbots, analytics and model training, with a checklist, penalty figures and questions for your AI vendor.

    October 26, 2026

    AI News

    Samsung Is Bringing More AI Into Health: What Does Connected AI Care Mean?

    Samsung is pushing AI deeper into Samsung Health and its connected device ecosystem. The wider lesson for enterprises is about turning continuous real-world sensor data into useful, private, trustworthy insight.

    August 20, 2026

    AI & Machine Learning

    Why Every SaaS Business Needs an AI-First Infrastructure Strategy Introduction

    The SaaS industry is entering a new phase. For years, success was driven by feature velocity, pricing models, and customer acquisition strategies. Today, intell

    August 4, 2026

    AI Governance

    How to Build a Responsible AI Governance Framework

    AI governance is no longer optional for enterprises. This guide walks through the key pillars of a responsible AI governance framework — from model documentation to audit trails and bias monitoring.

    July 10, 2026

    AI Engineering

    RAG vs Fine-Tuning: Which Approach Is Right for Your Enterprise LLM?

    Retrieval-Augmented Generation (RAG) and fine-tuning are the two primary approaches to customising large language models for enterprise use. Here is how to choose the right one for your use case.

    July 5, 2026

    AI Strategy

    AI Readiness Assessment: What Enterprise Leaders Need to Know Before Starting

    Before deploying AI, every enterprise must honestly assess its data infrastructure, team capabilities, and risk tolerance. This guide explains the key dimensions of an AI readiness assessment.

    June 28, 2026

    Cloud Engineering

    Cloud-Native Architecture for AI Workloads: A Practical Guide

    Running AI workloads at scale requires a cloud-native architecture purpose-built for performance, observability, and cost control. This guide covers the essential patterns every AI engineering team needs.

    June 20, 2026

    AI Strategy

    Build vs. Buy: Enterprise AI Platform Decisions

    Enterprises face a critical decision when adopting AI: whether to build a custom AI platform internally or integrate a commercial off-the-shelf solution. This choice significantly impacts cost, time, and strategic alignment.

    June 15, 2026

    AI Strategy

    Evaluating AI Vendors in 2026: An Enterprise Framework

    Enterprises are refining their approach to AI vendor selection. In 2026, evaluation criteria emphasize operational security, platform scalability, seamless integration, and robust governance.

    May 30, 2026

    ZigmaNeural is the enterprise AI and digital engineering brand of Zigmapeople Private Limited. Questions for the team: [email protected] or talk to our team.