The 12 Largest Machine Learning Companies In The World, And What They Do

largest machine learning companies

The 12 Largest Machine Learning Companies In The World, And What They Do

Machine learning has taken the world by storm. Almost every industry and company has a machine learning system, from Amazon to Walmart, Netflix to Google. Machine learning is everywhere, and it’s not going anywhere anytime soon. That’s why being informed about the largest machine learning companies in the world is important.

Not every company is using machine learning for the same purposes, or even in the same way. Certain companies are using it for different reasons and in a different manner from others. This is because companies use machine algorithms to solve different problems than other companies do.

You’ve probably heard the saying, “If all you have is a hammer, everything looks like a nail.” This is true of machine learning as well. If all you have is a machine learning algorithm, then every problem looks like a machine learning problem because that’s all there really is.

This article will provide an extensive overview of the 12 most popular machine learning companies in the world, ranked by the amount of funding raised.

#12: RepVue – $6 million

RepVue is a machine learning company founded in 2018. They track real-time sales compensation data for companies and then use their algorithm to rate them based on a set of criteria. They are headquartered in Chapel Hill, North Carolina.

RepVue deals with sales compensation data which relates to how well a company incentivizes its employees and how they sell to their clients. Their goal is to ensure the sales compensation data can be tracked online and remain transparent enough for a machine learning algorithm to assess.

#11: Apty – $12.9 million

Apty is a machine learning-based software tool integrated into the organization to help discover software and workflows in use throughout the business. Apty’s ultimate goal is to reduce the time it takes to integrate new technologies into existing processes.

It can find and analyze every piece of software being used by your company, including third-party tools and all components of those tools (inputs, outputs, etc.).

It then uses this data to create a strategic plan that predicts how different technology decisions will impact employee productivity and improve business processes. This company’s approach is unique in that it works for any company, and its impact on the organization will be much greater than simply creating better software.

#10: SuperAnnotate – $17.5 million

largest machine learning companies
SuperAnnotate enables the building of training data.

SuperAnnotate is a company whose primary focus is to apply artificial intelligence to the problem of training and annotating datasets used for computer vision pipelines.

The primary use of SuperAnnotate is for annotation, but in recent months, SuperAnnotate has been expanding its market by providing SaaS tools to other related industries, such as healthcare, finance, and advertising.

The company raised $17.5 million in its Series A funding round, led by Sequoia India and NEA.

#9: Algolux – $32.8 million

Algolux is an early-stage machine-learning company based in Quebec, Canada. It was founded by a group of students from Université Laval in 2014. These students wanted to create a solution to the problem of icy roads in Canada, so they developed a resolution called the Autonomous Vehicle Active Road Surfacing System (AVARS).

Algolux has received over $32 million in funding from investors, including Toyota AI Ventures and Groupe Renault. Car manufacturers, like Toyota, are currently using their products to test their autonomous vehicles (AV). Municipal governments also use the tech in the winter to clear roads of snow and ice.

Algolux uses advanced machine algorithms to design and produce hardware that can be installed onto different vehicles. Currently, the company is focusing on making self-driving cars that can perceive and respond to different road conditions while driving.

#8: Logically – $36.7 million

Logically is a threat intelligence startup founded in 2017. It combines artificial intelligence with human fact-checkers and OSINT investigators. Logically’s software is used by some of the largest firms in the world, including Facebook UK, which reported a 50% drop in hate speech after using it for 3 months. The company is based out of London, England.

Logically’s software can detect manipulated images and, according to Digital Journal, it can catch edited images in as little as 0.01 seconds. Their product allows clients to protect themselves from fake news, propaganda, slander, and the manipulation of information.

#7: Lookiero – $53.6 million

Lookiero was founded in 2016 in Bilbao, Spain. The company is led by CEO Oier Urrutia. It has a total of $53.6M in funding, the bulk of which came from its Series C in 2018.

Lookiero is a personal fashion shopping subscription service. It provides an algorithm for customers to find the most fashionable clothes online. The company’s goal is to create a new model for fashion delivery that syncs perfectly with today’s consumers who want faster and more personalized results at a cheaper price.

Lookiero ‘s technology, in combination with expanded collaborations with various fashion brands and more extensive global expansion, aims to make the process of finding the perfect shopping experience faster, easier, and cooler.

#6: Teikametrics – $65 million

Teikametrics is a SaaS machine learning company that was founded in 2015 and is located in Boston, Massachusetts. They are solely focused on eCommerce optimization and work along with retail giants.

Their system analyzes data pulled from thousands of online product SKUs to continuously optimize every aspect of an eCommerce platform, including pricing, inventory, and product performance.

The system is intelligent enough to automate many aspects of the optimization while providing trends in product performance. Teikametrics operates with the benefit of a large data set, which is the foundation of machine learning.

#5: Aidoc – $237.5 million

largest machine learning companies
Aidoc is an Israeli technology that specializes in healthcare AI.

Aidoc is a deep learning system that is capable of analyzing medical images to pinpoint critical anomalies. The platform is geared towards use by radiologists and has been proven to reduce the costs and workloads associated with repetitive tasks, such as image analysis.

They have been using deep learning to analyze medical images since 2016, when the company was first formed. The investment comes from a very successful Israeli venture capital firm. The company is now trying to advance the technology to an even higher level.

#4: Quantexa – $241 million

Quantexa provides a predictive analytics platform that automates the entire process of decision-making across a company’s operational workflow. It does this using machine learning algorithms to analyze data across a venture’s operational workflow (i.e., the flow of decisions that occur in the lifespan of a business venture) and develop plans to automate whole business sectors.

Quantexa automates the decision-making process by collecting data on a venture’s operational workflow and using machine learning to analyze this data.

The idea behind Quantexa is that they can collect data from every process across a venture and combine this data into one centralized platform, which will automatically allow Quantexa to create plans to automate entire operational decisions across multiple business sectors.

#3: Flock Safety – $380.6 million

Flock Safety is an AI company that has developed a camera system capable of notifying owners, security authorities, and local residents when a stolen vehicle enters the area.

The system uses a vehicle’s fingerprint, fed into the Flock Safety API, and matched with the Flock network of cameras. Once this process is complete, the vehicle is linked to its owners through the API and facial recognition software. This allows the owner to see who is driving his or her car via the Flock app.

When a vehicle is spotted, the owner can receive emergency notification and find out when it was last seen at home along with its route. The system also uses facial recognition to notify residents through the app, which allows them to take preventative actions.

Flock Safety is currently in the process of expanding its network to include more cities throughout North America.

#2: Arctic Wolf – $498.2 million

Arctic Wolf provides an AI-based cyber security solution that detects and prevents cyber attacks by catching anomalous user activity. The startup offers various security solutions, including Deep Learning-based fraud detection and click fraud protection, an anti-phishing solution, a solution for inside threats such as malicious insiders, and data breach detection.

Arctic Wolf’s algorithms can detect anomalies in a company’s users in a single day using thousands of parameters. This software has a technology platform that manages the artificial intelligence components and provides a customized security solution to each client.

The company was founded in 2012 in Eden Prairie, Minnesota, by former employees of Parvum Systems. The startup raised $498.2 million in funding from some of the world’s most prominent investors, including Spark Capital, NEA, and Google Ventures.

#1: UNISOC – $1.6 billion

largest machine learning companies
UNISOC is headquartered in Shanghai, China.

UNISOC uses machine learning algorithms to optimize chip production. The company’s algorithm can predict when a process is about to fail based on the data it processes.

UNISOC’s algorithm has made the company a dominant force in the chip production industry. This is an industry where speed and efficiency are of the utmost importance. In fact, predicting when a process will fail can make or break a company’s success.

Automation makes this possible, which is why UNISOC has grown so rapidly in recent years. They are sure to have a global reach in chip production by the time this article goes to print.

UNISOC is a Chinese-based technology company. Founded in 2001, UNISOC uses AI to customize and streamline the production of chips. The company’s algorithm can predict when a process is about to fail based on the data it processes. Overall, UNISOC has made the chip production industry much more efficient and profitable thanks to its use of automation.

The 12 Largest Machine Learning Companies In The World: Summary

1UNISOC – $1.6 billion
2Arctic Wolf – $498.2 million
3Flock Safety – $380.6 million
4Quantexa – $241 million
5Aidoc – $237.5 million
6Teikametrics – $65 million
7Lookiero – $53.6 million
8Logically – $36.7 million
9Algolux – $32.8 million
10SuperAnnotate – $17.5 million
11Apty – $12.9 million
12RepVue – $6 million

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Frequently Asked Questions

What is Machine Learning?

Machine learning is the science of getting computers to act without being explicitly programmed. In simpler terms, it’s about getting computer systems to act without programming them in advance.

What is the difference between machine learning and deep learning?

Machine learning doesn’t necessarily involve a neural network, while Deep Learning does. However, deep learning is a subset of machine learning.

What is the difference between algorithmic trading and machine learning?

Algorithmic trading involves preparing a list of rules, which are then applied to the markets. Algorithmic trading isn’t a subset of machine learning. Machine learning is a subset of algorithmic trading.

What does machine learning do?

Machine learning uses algorithms to make more accurate decisions than the human brain.

What is the difference between supervised and unsupervised machine learning?

Supervised machine learning involves a human labeling data, while unsupervised machine learning does not.

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