The Edge AI Ecosystem Image

The Edge AI Ecosystem

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Actionable Benefits

  • Identify the right solution partners for edge AI deployment, based on internal needs and requirements.
  • Understand current technology trends in edge AI, particular in TinyML.
  • Prepare product roadmaps with key features that meet market needs.

Critical Questions Answered

  • Who are the key SaaS and turnkey solution providers for edge AI?
  • What are the gaps and pain points in edge AI deployment?
  • How do cloud service providers position themselves in edge AI?

Research Highlights

  • A detailed breakdown of edge AI value chain.
  • Software and service features that are critical to edge AI deployment.
  • Market sizing of the edge AI ecosystem.

Who Should Read This?

  • Edge AI chipset suppliers.
  • Device and server OEMs.
  • Edge AI software and service providers.
  • System integrators.
  • Cloud service providers.

Table of Contents

1. EXECUTIVE SUMMARY

2. THE IMPORTANCE OF EDGE AI

2.1. Market Potential of Edge AI

3. CHALLENGES AND GAPS IN EDGE AI ADOPTION

4. FACILITATING EDGE AI DEPLOYMENT

4.1. Data Governance
4.2. Model Development
4.3. Model Optimization
4.4. Model Governance
4.5. Low-Code or Zero-Code Deployment
4.6. Operationalizing Edge AI

5. DEPLOYMENT ARCHITECTURE

6. ROLES OF KEY STAKEHOLDERS

6.1. Cloud Service Providers
6.2. Edge AI Chipset Vendors
6.3. Gateway and Server OEMs
6.4. IIoT Platform Developers
6.5. SaaS & Turnkey Service Vendors

7. MARKET FORECAST

8. RECOMMENDATIONS