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SmartData Collective > Exclusive > Top 8 Machine Learning Development Companies in 2022
ExclusiveMachine Learning

Top 8 Machine Learning Development Companies in 2022

Machine learning technology has led to some impressive changes that have helped companies with their testing approaches.

Alex Blackwell
Alex Blackwell
9 Min Read
companies use AI to improve their testing strategies
Shutterstock Photo License - Alexander Limbach
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Over 91% of leading businesses use AI technology. It has opened the door for companies to improve their business models in many ways.

Contents
Top ML Companies 1.      Brights2.      Dataiku 3.      Veda4.      IBM5.      DataToBiz 6.      Indium Software7.      Altoros8.     Digica

There are a number of great applications of machine learning. One of the biggest benefits is testing processes for optimal effectiveness.

The main purpose of machine learning is to partially or completely replace manual testing. Machine learning makes it possible to fully automate the work of testers in carrying out complex analytical processes. Based on the changes it has created, most experts agree that the primary goal of Machine Learning in this context is to reproduce more accurate predictions. This will allow marketers, business owners, and IT-sphere employees to make the right decisions in developing and creating new products.

As a result of the activity of artificial intelligence, the machine learns, remembers, and reproduces the correct option. ML opens up new opportunities for computers to solve tasks previously performed by humans and trains the computer system to make accurate predictions when inputting data. One example is using machine learning tools like Selenium to test web development processes. It stimulates the growth of the potential of artificial intelligence, being its indispensable assistant and, in the view of many, even a synonym.

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Machine learning is used in many industries. It allows for optimizing the work of banks, restaurants, factories, and even gas stations. It is also often found in Internet sales and the organization of chatbots. It applies to any workflow implemented in software – not only within the traditional business part of enterprises but also in research, production processes, and, increasingly, the products themselves. Machine learning can now compete with the precision of even surgeons. Instead of specifying what the software should look for, programmers “teach” the XI using a collection of applied images. Companies that work on machine learning for health care, like Google, create large groups of medical images selected by physicians. Machine learning algorithms use these sets of visual data to look for statistical patterns to identify which image features allow you to assume that it is worthy of a particular label or diagnosis.

Neptune shared a blog post on the benefits of using AI to improve testing capabilities. Many other companies have shared even more interesting benefits of using machine learning in testing.

Top ML Companies 

Data is called the new oil: by analyzing information, predicting key business parameters, and finding better solutions, you leave your competitors far behind. That’s why partnering with ML companies is a great solution to bring the latest innovative technology and solutions into the business so that organizations improve service, anticipate the future, automate processes, increase and drive sales, reduce costs in production and prevent risk. Here are the top 8 trusted partners:

1.      Brights

Our leader has more than 100 employees and over 400 successful cases for clients from different parts of the world – this is the Brights. The company is already 11 years and growing. Brights’ machine learning experts can help you and your business explore new privileges and learn more. The company develops custom solutions for automating the processes of large companies and startups from scratch. Most often, these are turnkey projects: Brights independently design, conduct research, prototyping, and testing. 

2.      Dataiku 

Dataiku is an AI software and machine learning company that offers AI services to democratize data. The company believes that business empowerment is possible through data services and collaboration. Dataiku provides various AI tools and software to help with customer churn, fraud detection, supply chain optimization, predictive maintenance, and more. Everyday AI is a core concept of Dataiku, where the systematic use of data for everyday operations makes businesses competent to succeed in competitive markets. Dataiku helps its customers at every stage, from data preparation to analytics applications, to implement a data-driven model and make better decisions. 

3.      Veda

Veda technologies enable faster data processing, task automation, and organization of patient information. With ML capabilities, these tools eliminate errors and process data at a rapid pace. As a result, medical organizations can complete file processing within 24 hours. The company’s solutions solve repetitive and data-related tasks, allowing medical facilities to work more efficiently and physicians to focus their energy on patient care.

4.      IBM

IBM is primarily known for its own artificial intelligence engine used in research and commercial products. It offers AI for decision-making, language processing, and intelligent task automation. Watson was initially designed to compete with humans in games such as Jeopardy. Today, their technology can be integrated into virtually any workflow, from human resources to finance to supply chain management.

5.      DataToBiz 

DataToBiz is one of the most promising AI companies of our time. The company analyzes AI and big data and helps organizations manage their data resources and find the best ways to extract information from data so they can make data-driven decisions. DataToBiz offers comprehensive solutions to help businesses succeed with advanced technologies such as machine learning, artificial intelligence, and data science. The company’s solutions are flexible, scalable, and cost-effective. The team has years of experience and a satisfaction rate of over 97% because it dives deep into data to uncover its essence and dares to act.  The company is a certified partner of Google Cloud, Microsoft Azure, and AWS. It helps enterprises overcome challenges by implementing data-driven models. 

6.      Indium Software

Indium Software is a leading provider of digital engineering solutions with deep expertise in application development, cloud engineering, data and analytics, DevOps, Digital Assurance, and gamification. Indium’s key differentiators are its specialization in low-code development, Ai text analytics, and partnerships with technology companies such as Mendix, AWS, Denodo, and Striim. The company works with clients from around the world. Indium Software provides AI & ML services to develop self-learning algorithms, learn from data and draw conclusions without human intervention. Industry influencers such as Forbes, Dun & Bradstreet, and Clutch have recognized us as trusted digital engineering partners for innovative startups and promising enterprises.

7.      Altoros

Altoros is an experienced IT service provider that helps enterprises improve operational efficiency and accelerate product innovation by reducing time-to-market. Our customers gain a sustainable competitive advantage by leveraging the power of cloud automation, microservices, AI/ML, and industry expertise. Altoros AI solutions help companies handle routine tasks. Altoros has five global offices. The company has 18 years of experience and has completed 1400 projects. It is headquartered in Silicon Valley.

8.     Digica

Digica researches, implements, and commercializes intelligent software across the AI spectrum, focusing on deep learning in computer vision and “AI at the edge.” Digica’s strength is the combination of its expertise in AI with world-class software development. The company works with large companies and innovative startups in many industries, including automotive, defense, medical, technology, and telecommunications. Digica is committed to advancing AI and is fueled by the rapid growth of smart devices at the network’s edge – smartphones, smartwatches, and sensors installed on machines and infrastructure.

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