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Architecting AI Software Systems

You're reading from   Architecting AI Software Systems Crafting robust and scalable AI systems for modern software development

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Product type Paperback
Published in Oct 2025
Last Updated in Oct 2025
Publisher Packt
ISBN-13 9781804615973
Length 212 pages
Edition 1st Edition
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Authors (2):
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Richard D Avila Richard D Avila
Author Profile Icon Richard D Avila
Richard D Avila
Imran Ahmad Imran Ahmad
Author Profile Icon Imran Ahmad
Imran Ahmad
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Toc

Table of Contents (14) Chapters Close

Preface 1. Architecting Fundamentals
2. Fundamentals of AI System Architecture FREE CHAPTER 3. The Case for Architecture 4. Software Engineering and Architecture 5. Architecting AI Systems
6. Conceptual Design for AI Systems 7. Requirements and Architecture for AI Pipelines 8. Design, Integration, and Testing 9. Architecting a Generative AI System – A Case Study 10. Insights and Future Directions 11. Unlock Your Book’s Exclusive Benefits 12. Other Books You May Enjoy
13. Index

Integration and testing

While architects don’t play a major role in integration – primarily done by implementation engineers – integration issues inevitably arise. Architects are consulted to aid in design changes while maintaining system conceptual integrity.

Types of integrations

Several integration approaches exist, each with distinct advantages and challenges for AI system development.

Figure 6.5: Integration approaches comparison

Figure 6.5 provides a visual comparison of four common integration strategies. The top-down approach (blue) begins with the main module and progressively integrates lower-level components, allowing early validation of high-level architectural concepts. The bottom-up approach (green) starts with the smallest components and builds upward, ensuring well-tested foundations before system-level integration begins.

The parallel approach (orange) develops independent integration streams that eventually merge at a...

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