Edge ML Enablement: Development Platforms, Tools, and Solutions

Publish Date: 12 May 2022

Code: AN-4958

Research Type: Report

Pages: 28

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RELATED SERVICE: AI & Machine Learning

Actionable Benefits

Actionable Benefits

Introduce readers to the edge ML enablement market.
Understand impactful technological and market trends that drive edge ML development.
Educate businesses on leveraging the skills of edge ML enablement vendors in their AI journey.

Research Highlights

Research Highlights

Analysis of enabling technologies in edge ML enablement.
A detailed overview of key edge ML enablement vendors.
Market sizing of the edge ML enablement market.

Critical Questions Answered

Critical Questions Answered

Who are the key edge ML enablement vendors and what do they offer?
Why are they important to the edge ML market?
What differentiates the different product offerings?

Who Should Read This?

Who Should Read This?

Edge ML implementers that are looking for external support.
Strategy planners and advisors within the edge AI industry.
System integrators helping businesses to implement edge ML applications.

Table of Contents

1. EXECUTIVE SUMMARY

2. KEY MARKET DRIVERS

2.1. Diverse Hardware Ecosystem

2.2. Compliance with Data Privacy Regulations

2.3. Lack of Big Data

2.4. Cost of Development

3. KEY TECHNOLOGIES

3.1. Data Management

3.2. Model Design

3.3. AutoML

3.4. Edge MLOps

4. VENDOR ECOSYSTEM

4.1. AWS

4.2. Blaize

4.3. DeGirum

4.4. Edge Impulse

4.5. Google and Qualcomm

4.6. Imagimob

4.7. Latent AI

4.8. MicroAI

4.9. Microsoft

4.10. Neuton

4.11. Nota

4.12. NXP

4.13. Plumerai

4.14. Qeexo

4.15. SensiML

4.16. STMicrolelectronics

4.17. Syntiant

5. MARKET FORECAST

6. KEY RECOMMENDATIONS

6.1. Recommendations for Vendors

6.2. Recommendations for ML Implementers and End Users

Companies Mentioned