Ultimate Snowflake Cortex AI for Generative AI Applications

Key Features
? Build enterprise-ready GenAI apps using Snowflake Cortex tools and APIs.
? Implement RAG, AI Agents, and Document AI with real-world precision.
? Explore practical Cortex use cases across industries and domains.

Book Description
Snowflake Cortex is redefining how modern enterprises build, scale, and deploy Generative AI—natively within the data cloud.

Ultimate Snowflake Cortex AI for Generative AI Applications is a hands-on, end-to-end guide designed for data professionals, engineers, and technical leaders eager to unlock the full power of Snowflake’s native AI engine. The book begins by grounding you in the fundamentals of AI/ML within the Snowflake ecosystem before diving deep into the architecture, capabilities, and use cases of Snowflake Cortex.

As you progress, you’ll explore Cortex’s built-in machine learning functions, dive into prompt engineering, Retrieval-Augmented Generation (RAG), and learn how to leverage LLM functions effectively. You’ll gain hands-on experience in fine-tuning models, translating natural language queries into actionable insights, and automating document processing using Cortex’s Document AI. Practical chapters on security, governance, and cost discipline ensure you’re prepared for enterprise-scale AI deployment.

With real-world case studies and cross-industry applications, this book equips you with both the strategic understanding and technical skills to implement Generative AI at scale. Cortex is the future of enterprise AI—don’t just adapt to it, lead it.

What you will learn
? Build and deploy Generative AI apps using Snowflake Cortex.
? Understand and apply Cortex’s built-in LLM functions effectively.
? Fine-tune LLMs for domain-specific, enterprise-grade applications.
? Use RAG and prompt engineering for accurate AI responses.
? Extract insights from structured and unstructured enterprise data.
? Automate document workflows using Cortex’s Document AI features.
? Solve cross-industry problems with real-world Cortex implementations.

Table of Contents
1. Introduction to AI/ML in the Snowflake Ecosystem
2. Understanding Snowflake Cortex
3. Overview of Machine Learning Functions
4. Introduction to LLMs, Prompt Engineering, and RAG
5. LLM Functions in Cortex AI
6. Fine-Tuning Large Language Models in Cortex
7. Natural Language Queries to Actionable Insights
8. Unlocking Document Intelligence with Document AI
9. Implementing Cortex with Security, Governance, and Cost Discipline
10. Industry Use Cases and Case Studies
11. Conclusion and Next Steps
Index

About the Authors
Krishnan Srinivasan holds a Master of Technology degree in Data Science and Engineering and brings over 25 years of diverse, cross-domain experience across cutting-edge technologies, specializing in Data, Artificial Intelligence, Analytics, and Cloud AI. He began his career as a data professional, working on pioneering data warehousing and analytics initiatives that laid a strong foundation for building scalable, data-driven solutions. His deep engagement with enterprise data systems and strong passion for innovation led him into the field of Artificial Intelligence. This progression, from data to AI, enabled him to bridge the gap between traditional analytics and modern AI, positioning him to lead transformative AI initiatives at the intersection of data and intelligence. Throughout his distinguished career, Krishnan has partnered with numerous Fortune 500 clients across the globe, designing and delivering impactful solutions across a wide range of industries.