Ultimate AI-Powered App Development with Kotlin

Build Android Apps That Think, Learn, and Respond.

Key Features
● Get a free one-month digital subscription to www.avaskillshelf.com.
● Real-world Android AI projects covering sentiment analysis, recommendation systems, and conversational AI.
● On-device machine learning with LiteRT, ML Kit, and deep learning models optimized for Android.
● End-to-end Android AI development from Kotlin fundamentals and Jetpack Compose to production deployment.

Book Description
Don't Just Build Android Apps. Build Apps with Intelligence.

AI-powered mobile applications are no longer the domain of specialists — and Android developers who can integrate on-device ML, generative AI, and conversational interfaces are defining the next generation of intelligent apps. Ultimate AI-Powered App Development with Kotlin takes you from Kotlin fundamentals and Android essentials through machine learning (ML), on-device AI, LiteRT, ML Kit, and modern AI services, including Gemini and ChatGPT.

The book takes a hands-on approach with practical projects showing how these technologies work together in real Android applications. You build a sentiment analysis app, an on-device recommendation system, and a conversational AI application using Gemini and ChatGPT, learning how to integrate models, work with AI services, optimize applications for mobile devices, and create responsive interfaces with Jetpack Compose throughout.

By the end, you will be able to design, build, test, optimize, and deploy AI-powered Android applications with the practical skills needed to bring intelligent features to production mobile products.

What you will learn
● Build Android applications using Kotlin and modern Android development practices.
● Integrate ML models into Android applications using LiteRT and ML Kit.
● Run and optimize on-device ML models directly on Android hardware.
● Build practical sentiment analysis and recommendation applications for Android.
● Integrate Gemini and ChatGPT to build conversational AI Android applications.
● Design, test, secure, and deploy AI-powered Android applications to production.

1. Introduction to Kotlin and AI in Mobile Apps
2. Understanding Kotlin Basics
3. Deep Dive into Kotlin
4. Building Your First Android App
5. Getting Started with Machine Learning
6. Deep Learning For Mobile Apps
7. Natural Language Processing on Mobile with LiteRT
8. Object Detection and Image Segmentation
9. Recommendation System and Personalization
10. Designing User-Centric AI Apps
11. Project: Sentiment Analysis of User Input with TensorFlow
12. Image Processing Using ML Kit
13. Project: Contextual AI Assistant
14. Testing and Optimization
15. Deploying Your AI App
16. The Future of AI in Mobile Apps
Index

Pankaj Kumar is a Mobile Architect with 15+ years of experience designing secure, scalable mobile applications across Banking, FinTech, and PropTech. His expertise spans Android, Kotlin, mobile architecture, security, performance, LiteRT, model optimization, and AI integration. He has led engineering teams and built AI-powered products, with a focus on AI guardrails and responsible AI integration.

About the Technical Reviewer
Imran Solanki is a Senior Consultant and Software Architect with over 13 years of experience building scalable software systems across telecommunications, health tech, IoT, logistics, and finance. Passionate about artificial intelligence and modern software engineering, he helps organizations build intelligent, cloud-native applications that solve real-world problems. Imran enjoys mentoring developers through teaching, technical workshops, and conference talks. Born and raised in Pune, with roots in Mandrella (Jhunjhunu), Rajasthan, Imran lives with his parents, wife, and three children. This book reflects his passion for combining AI with sound engineering principles to build reliable, practical software.

Anuj Ashok Potdar is a Senior Software Engineer at Kayak, an AI researcher, and a Java expert specializing in secure distributed systems and Trustworthy AI. A graduate of Northeastern University, Anuj is an accomplished software engineer with a robust background in designing scalable Java microservices, event-driven architectures, and distributed systems.

Amirtha Saminathan is a Lead Software Engineer with nearly two decades of experience designing and modernizing enterprise applications across retail, financial services, and energy domains. Her expertise spans Java, Kotlin ecosystem technologies, Spring Boot, microservices, cloud platforms, Kubernetes, event-driven architectures, and enterprise AI.

Throughout her career, Amirtha has contributed to large-scale digital transformation initiatives, building scalable systems that improve operational efficiency, customer experiences, and business decision-making. Her current interests focus on practical enterprise AI, including AI-powered application development, responsible AI adoption, governance, explainability, and the integration of intelligent capabilities into business-critical systems.

Beyond her engineering work, Amirtha contributes to the broader technology community as a technical reviewer and innovation judge, evaluating emerging technologies, AI solutions, and software engineering practices. She brings to this book a practitioner’s perspective, emphasizing technical accuracy, real-world applicability, maintainability, and effective AI integration in modern application development