AI On-device Tools Market Research Report - Size, Share, Growth, and Trend Analysis | Forecast (2025 - 2030)

Chapter 1. Global AI On-device Tools Market– Scope & Methodology

• 1.1 Market Segmentation
• 1.2 Scope, Assumptions & Limitations
• 1.3 Research Methodology
• 1.4 Primary Sources
• 1.5 Secondary Sources

Chapter 2. Global AI On-device Tools Market– Executive Summary

• 2.1 Market Size & Forecast – (2025 – 2030) ($M/$Bn)
• 2.2 Key Trends & Insights
• 2.2.1 Demand Side
• 2.2.2 Supply Side
• 2.3 Attractive Investment Propositions
• 2.4 COVID-19 Impact Analysis

Chapter 3. Global AI On-device Tools Market– Competition Scenario

• 3.1 Market Share Analysis & Company Benchmarking
• 3.2 Competitive Strategy & Development Scenario
• 3.3 Competitive Pricing Analysis
• 3.4 Supplier-Distributor Analysis

Chapter 4. Global AI On-device Tools MarketEntry Scenario

• 4.1 Regulatory Scenario
• 4.2 Case Studies – Key Start-ups
• 4.3 Customer Analysis
• 4.4 PESTLE Analysis
• 4.5 Porters Five Force Model
• 4.5.1 Bargaining Power of Suppliers
• 4.5.2 Bargaining Powers of Customers
• 4.5.3 Threat of New Entrants
• 4.5.4 Rivalry among Existing Players
• 4.5.5 Threat of Substitutes

Chapter 5. Global AI On-device Tools Market– Landscape

• 5.1 Value Chain Analysis – Key Stakeholders Impact Analysis
• 5.2 Market Drivers
• 5.3 Market Restraints/Challenges
• 5.4 Market Opportunities

Chapter 6. Global AI On-device Tools Market– By Type

• 6.1 Introduction/Key Findings
• 6.2 Machine Learning Libraries
• 6.2.1 TensorFlow Lite
• 6.2.2 PyTorch Mobile
• 6.2.3 Core ML
• 6.2.4 Google ML Kit
• 6.3 Edge AI Platforms
• 6.3.1 NVIDIA Deep Learning AI
• 6.3.2 Microsoft Azure Edge AI
• 6.3.3 Apple Create ML
• 6.3.4 Run.ai
• 6.4 AI Optimization Tools
• 6.4.1 Edge Impulse
• 6.4.2 KUNGFU.AI
• 6.5 Y-O-Y Growth trend Analysis By Type
• 6.6 Absolute $ Opportunity Analysis By Type , 2025-2030

Chapter 7. Global AI On-device Tools Market– By End User

• 7.1 Introduction/Key Findings
• 7.2 Consumer Electronics
• 7.2.1 Smartphones
• 7.2.2 Wearables
• 7.2.3 Smart TVs
• 7.3 Automotive
• 7.3.1 Autonomous Vehicles
• 7.3.2 In-car AI systems
• 7.4 Industrial Automation
• 7.4.1 Predictive Maintenance
• 7.4.2 Robotics
• 7.4.3 Smart Manufacturing
• 7.5 Healthcare
• 7.5.1 Mobile Health Devices
• 7.5.2 Remote Patient Monitoring
• 7.5.3 Diagnostic Tools
• 7.6 Retail
• 7.6.1 In-store AI tools
• 7.6.2 AI-powered checkout systems
• 7.7 Y-O-Y Growth trend Analysis By End User
• 7.8 Absolute $ Opportunity Analysis By End User , 2025-2030

Chapter 8. Global AI On-device Tools Market, By Geography – Market Size, Forecast, Trends & Insights

Chapter 9. Global AI On-device Tools Market– Company Profiles – (Overview, Type Portfolio, Financials, Strategies & Developments)

• 9.1 TensorFlow Lite
• 9.2 Edge Impulse
• 9.3 Core ML
• 9.4 Google ML Kit
• 9.5 NVIDIA Deep Learning AI
• 9.6 Microsoft Azure Edge AI
• 9.7 Apple Create ML
• 9.8 Run.ai
• 9.9 PyTorch Mobile
• 9.10 KUNGFU.AI