AI-Powered Apps in Google Workspace

Build Production-Ready Assistants, Dashboards, and RAG Systems with Apps Script & Gemini

De: Laurence Lars Svekis

Narrado por: Virtual Voice

AI-Powered Apps in Google Workspace Build Production-Ready Assistants, Dashboards, and RAG Systems with Apps Script & Gemini

Most books on AI teach you how to build demos. This book teaches you how to build real AI-powered applications.

AI-Powered Apps in Google Workspace is a practical, systems-focused guide for developers, indie hackers, educators, and SaaS builders who want to embed artificial intelligence directly into Google Docs, Google Sheets, and web apps—without hallucinations, brittle prompts, or unreliable results.

Instead of treating AI as magic, this book shows you how to design trustworthy AI systems using Retrieval-Augmented Generation (RAG), embeddings, vector search, and chat memory—all implemented with Google Apps Script and Gemini.

What You’ll Learn
You’ll build a complete AI foundation that works across multiple interfaces:

• AI assistants inside Google Docs that explain, summarize, and answer questions using document content
• AI assistants inside Google Sheets for analytics, dashboards, and semantic search
• A shared vector store using embeddings for fast, accurate retrieval
• Chatbots with memory and follow-up support that behave consistently
• A standalone web app chat UI powered by the same RAG system
• Guardrails that force AI to refuse when information is missing

Every example in this book is fully implemented, tested, and reusable.

Why Retrieval-Augmented Generation (RAG) Matters

Large language models don’t “know” your pricing, policies, or internal documentation.

Without retrieval, they guess—and guessing leads to hallucinations.

This book makes RAG a first-class design principle:

1. Index real content from Docs and Sheets
2. Generate embeddings
3. Retrieve relevant sources
4. Force the model to answer only from those sources

If the answer isn’t in your data, the AI must say so.

That’s how reliable AI products are built.

Why Google Workspace?

Google Workspace already contains your most valuable knowledge:
• Product documentation
• Pricing tables
• Policies and procedures
• Metrics and reports

This book shows you how to turn Google Workspace into an AI application platform, using:
• Google Apps Script
• Gemini models
• Embeddings and vector search
• Native permissions and access control

No servers to manage.
No complex infrastructure.
No cloud setup required.

Who This Book Is For

This book is ideal for:
• Developers and JavaScript programmers
• Indie hackers and SaaS builders
• Educators and internal tools teams
• Anyone building AI features that must be correct, explainable, and maintainable

You don’t need prior AI or machine-learning experience—just basic JavaScript familiarity and a desire to build systems that work.

What Makes This Book Different

✔ Focuses on systems, not prompts
✔ Uses real data, not placeholders
✔ Includes chat memory, refusal logic, and testing workflows
✔ Builds one shared AI foundation used across multiple apps
✔ Designed for production thinking, not novelty

This is not a collection of tips.

It’s a complete architecture.

About the Author

Laurence Svekis is a Google Developer Expert (GDE) for Google Workspace and Apps Script and has taught over two million students worldwide through his courses, books, and tutorials. With nearly two decades of experience teaching web development and application design, Laurence specializes in breaking down complex systems into practical, real-world solutions.

If you want to move beyond AI demos and start building AI-powered applications people can actually trust, this book will show you how.