Strengths of MLOps Platform, Technology Competition with International Companies

A British media has selected 20 companies that use MLops. Let's take a look at how competitive is in terms of technology.

Featured image MLOps Platform Keeps Up with International Companies

The UK’s TNW focused on new technologies and start-ups, listing the comparison of global top 20 companies’ MLOps capabilities.

Based on this information, I prepared today’s posting based on the current status of introduction of MLOps technology by AI solution providers and comparing it to’s technology.

Introduction of the current status of MLOps functions of 20 global companies

As I mentioned in my previous post, “The Obstacles and Solutions of MLOps,” the function and utility of MLOps are currently very high-profile among experts dealing with data.

TNW is schematicizing and introducing the functions of various global companies and startups that support MLOps in line with that trend.

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(TNW Selected TOP 20 Companies' MLops Technology Status)

First of all, it is divided into four main categories.

  1. Data Acqusition and Preparation
  2. Model Development and Training
  3. Model Deployment and Operations
  4. System-wide Features
    We said that “The current AI market is too fragmented,” in a posting titled “Next Generation Automated AI Development Platform,” that introduced our MLOps platform.

The table alone shows that companies that perform most of the different functions of MLOps are not fully prepared in many areas except for Amazon, Microsoft, and IBM worldwide.

In particular, during the second stage of model development and testing, many companies perform data learning using machine learning, but later, they show poor performance in model management.

MLOps technology at

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(MLOps on supporting many features in addition to Accelerator Support) offers all the capabilities of the standard except to provide Accelerator Support, the accelerator needed for certain highest-level models that take a long time to learn.

  1. Data Acquisition and Preparation → Utilize customer data using DS2 Dataset and collect quality data through Public Data. Data processing and preparation using Labeling AI afterwards.

  2. Model Development and Training → AI development and testing using Click AI.

  3. Model Deployment and Operations & System-wide Features → Distribution and monitoring of AI models using Skyhub AI and maintenance through re-learning.

And when all of this is over, we can make free AI trading available in the AI Market.


Today, we introduced our strengths in comparison to other MLOps providers with the features of and posting about the concept of MLOps.

We promise you that you will be able to check our platform in the future with reliable external materials, and we will come back with a different topic.

References : TNW News

Visit our MLOps platform DS2.AI and check out the various MLOps solutions we offer!