As data volumes increase exponentially, enterprises are adopting AI and ML capabilities to gain business insights and make decisions. However, enterprises face several challenges in deploying ML models to production. As a result, enterprises are leveraging Machine Learning Operations (MLOps) for their deployment, monitoring, and collaboration needs to improve the quality and relevance of ML model results, achieve business-oriented outcomes, and enhance stakeholder experience. MLOps is a growing market, rapidly evolving in terms of product features, architecture, training and support, deployment options, partner ecosystem, and commercial models. Technology providers can help enterprises succeed in their AI/ML transformation journeys by implementing MLOps across the enterprise.

In this research, we present detailed profiles and assessments of 18 technology providers featured on Everest Group’s MLOps Products PEAK Matrix® 2022. Each profile provides a comprehensive picture of the technology provider’s size and scope of business, product capabilities, partnerships, domain investments, and case studies.

Scope

• The assessment is based on Everest Group’s annual RFI process for the calendar year 2022, interactions with leading MLOps providers, client reference checks, and an ongoing analysis of the MLOps products landscape
• All industries and geographies

Contents

This report features:

• Everest Group’s PEAK Matrix® evaluation of MLOps technology providers and their categorization into Leaders, Major Contenders, and Aspirants
• An overview of MLOps and key challenges in scaling AI
• Key ML platform technology trends
• A detailed assessment of the strengths and limitations of 18 MLOps technology providers in terms of their market impact and vision & capability

Membership(s)

Data & Analytics

Sourcing and Vendor Management