Product guide

RAG-Driven Generative AI: MAS-RAG with Oracle Database 23ai, 2nd Edition

MAS-RAG: RAG-Driven Generative AI is a second-edition technical book about building multi-agent retrieval-augmented generation systems with Oracle Database 23ai. It covers hybrid vector and SQL retrieval, GraphRAG, Spatial-RAG, video pipelines, and human-feedback workflows. The listing assumes comfort with Python and basic machine-learning concepts.

At a glance

Explains DualRAG, combining vector search with SQL filtering for structured enterprise data.
Covers vector search, GraphRAG, and Spatial-RAG in Oracle Database 23ai.
Topics include multi-agent RAG architecture, adaptive retrieval, multimodal video, and human feedback.
The contents include examples such as conversational agents and a live recruiter agent.

Price

$43.99Save 20%

Reference price: ~~$54.99~~

Price checked: Nov 14, 2026

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Pros and cons

Pros

Combines retrieval approaches for structured and unstructured data rather than focusing only on vector search.
The contents span database-backed RAG, multi-agent workflows, graph and spatial retrieval, and video use cases.
Audience guidance makes the expected Python and machine-learning background explicit.

Cons

Readers without Python comfort or basic machine-learning knowledge may find the material difficult to follow.

Technical specifications

9 specifications

Publication details
Publisher	Packt Publishing
Edition	2nd ed.
Publication date	April 17, 2026
Language	English
Print length	430 pages
ISBN-10	1807424952
ISBN-13	978-1807424954

Physical details
Dimensions	7.5 x 0.97 x 9.25 inches
Weight listed	1.62 pounds

What to know before buying

The free DRM-free PDF and Packt Reader access require email sign-up and proof of purchase.

Who is it for?

A good fit for

AI and ML engineers building retrieval-augmented applications on enterprise data.
Data scientists and MLOps professionals exploring multi-agent RAG and human-feedback workflows.
Database engineers, software developers, and solution architects integrating language models with structured and unstructured data.

Less suited to

Readers seeking a beginner introduction that does not assume Python and basic machine-learning knowledge.
Readers who want a broad, database-agnostic overview rather than material centered on Oracle Database 23ai.

Customer reviews on Amazon

4.8 / 5 · 7 ratings

5 stars82%82%
4 stars18%18%
3 stars0%0%
2 stars0%0%
1 star0%0%

Aggregate customer ratings lean strongly toward the top end, but the sample is small and no written feedback is supplied. That offers limited evidence about how readers judge the book. Prospective buyers should base fit primarily on the listed Oracle-focused coverage and the stated Python and machine-learning prerequisites.

Frequently asked questions

What topics does this book cover?

The listing describes DualRAG and hybrid vector-plus-SQL retrieval, GraphRAG, Spatial-RAG, multi-agent RAG, and multimodal video pipelines, with Oracle Database 23ai as a central platform.

What background does the book expect?

The listing says readers should be comfortable with Python and have a basic understanding of machine-learning concepts. Prior generative-AI or vector-database experience may help.

Is a digital copy included?

The listing claims a free DRM-free PDF and Packt Reader access with the book. Email sign-up and proof of purchase are required.