machine learning

What Are the Top Machine Learning Startups to Look at for Inspiration?

Machine learning is making computers smarter. By using various algorithms and statistical models, computers can perform a task without explicit instructions. In the place of instructions, patterns and observations are used to make a decision.

Machine learning has gained increasing popularity in recent years. Businesses and organizations have vast amounts of data available that they can use to make better decisions.

With the help of machine learning, companies can optimize their processes, which saves them money and maximizes their profits.

Startups are also paying a lot of attention to machine learning. Several machine learning startups are making quite an impact. For instance, take live chat apps for websites as an example; they are also moving towards building chatbot options. However, it is totally a different debate about how effective these chatbots are.

Here are the top machine learning startups to gain inspiration from:

  1. Behavox

Businesses want to make their employees as productive as they can be. Companies also want their employees to be happy with their organization so they’ll stick around for a longer period of time.

In the past, businesses used to conduct surveys and ask employees in person. But actions speak louder than words, and a startup named Behavox is using machine learning to understand and make sense of an employee’s actions.

Behavox is a platform that is revolutionizing the workplace. Using machine learning, the company can identify employee behaviors based on the actions that an employee takes.

By identifying patterns in employee behavior, this startup can provide valuable insights, which include employee motivation, compliance, creativity, and productivity.

Behavox is a startup to look out for, given the fact that it made it to the Forbes Fintech 50 for 2019.

It has offices in New York, London, San Francisco, Montreal, and Singapore.

  • SenseTime

Computer vision has a large number of applications, from facial recognition to object detection, scene understanding to pattern recognition. Several problems still need to be solved with the help of computer vision.

SenseTime is a Software As A Service (SaaS) company that works on artificial intelligence and machine learning. It started as an academic project by Tang Xiao’ou, a professor at the Chinese University of Hong Kong (CUHK) and a computer scientist, Xu Li.

SenseTime was founded in Hong Kong in 2014, and within four years of its inception, it has grown into an absolute giant. It has been valued at $7.5 billion in 2019.

It primarily focuses on computer vision, as well as deep learning, facial recognition, object detection, and other related areas. In 2014, SenseTime showcased a facial recognition algorithm that had better detection accuracy than human eyes.

SenseTime also has a large number of clients; around 700 of them, including the Massachusetts Institute of Technology (MIT), Huawei, Xiaomi, Alibaba, and others. Moreover, it also has partnerships with different educational institutions such as Tsinghua University, Peking University, Shanghai Jiao Tong University, and Zhejiang University.

  • Alation

Businesses have been storing data about their business for quite some time now. But, not every company is utilizing this data to gain insights that could take them to the next level.

Without extracting insights, the data stored by a business is useless. To be able to deal with increasingly tech-savvy competitors, companies need to use the data at their disposal to make better decisions.

Alation is a data catalog that provides solutions for four dominant personas, which include Chief Data Officer, Analyst, Steward, and IT & Engineering.

A data catalog is a fully organized service that allows users to investigate and understand the required data, while at the same time helping organizations to gain more value.

Alation uses machine learning to automatically index data according to its source. It continually improves the human understanding of data. Furthermore, it is known for its intuitive design and ease of use.

Alation facilitates collaborative analysis uniformly, making it easier for teams to analyze the same data. Reputable institutions like eBay, GoDaddy, Munich RE, the city of San Diego, Pfizer, have adopted the Alation data catalog.

  • DataRobot

Data science is a relatively new field, and people who are experts in the area are few and far between. Data scientists have to do several processes before they can derive insights from data. These steps can take weeks and even months if the data is challenging to work with or exceptionally large.

DataRobot is an automated machine learning platform that allows users to create highly accurate predictive models all at the cost of a mouse click. DataRobot has previously raised a total of $224.6M in funding over seven rounds.

DataRobot reduces the workload for data scientists so that they may focus on the things that matter the most, making predictions and getting insights.

All you need to use DataRobot is to prepare your dataset, do some drag and drop, automatically evaluate several models, monitor and manage the models, and derive insights and make predictions. It’s that simple. 

Data scientists can improve their productivity by using DataRobot. They’ll be able to work on more projects because they’ll have more time available to them.

DataRobot uses the most modern open-source algorithms and is available on the cloud, on-site, or even as a completely manage artificial intelligence service.  

  • Benevolent AI

The pharmaceutical industry faces some challenges. Discovering new medicine is becoming increasingly difficult. The industry, as a whole, needs multiple reforms.

Benevolent AI is a major disruptor for the pharmaceuticals. It is a computational and experimental discovery platform that gives scientists new opportunities and ideas to find cures for diseases.

Using machine learning and artificial intelligence, Benevolent AI allows new medicines to be discovered, developed, tested, and revealed to the market.

Benevolent AI focuses on the four major processes in drug discovery. These are target identification, knowledge architecture, molecular design, and precision medicine. 

In 2018, the startup brought its total funding to more than $200 million.

Benevolent AI is headquartered in London and has locations in New York, Cambridge, and Antwerp.

  • LogiNext

Logistics is a vital business process. Without sound logistics, a business cannot run smoothly. Optimizing logistics is a difficult task. In the past, executives weren’t able to make decisions using real-time data, which significantly reduced the effectiveness of their choices.

LogiNext is a startup that uses machine learning and artificial intelligence to come up with solutions for different kinds of logistics. It is the quickest growing SaaS (Software As A Service) company in the fields of workforce and logistics optimization. Alibaba supports LogiNext through its funded One97 Communications Ltd.

The company provides solutions for on-field workforce optimization, real-time tracking, resource automation allocation, and route optimization.

LogiNext was founded in 2014, and its headquarter regions include the West Coast, Silicon Valley, and San Francisco Bay Area. Its total funding amount is $10.6 million.


Revenue management, also known as yield management, predicts consumer behavior and optimizes product availability and price, to maximize growth. Revenue management is essential because every business depends on revenue for survival.

Revenue also tells a lot about how a business is doing and if it’s business processes are optimized or not. By focusing on revenue generation, LMS companies can also increase their profitability. is a revenue intelligence platform that is robust and all-encompassing for revenue management.

Using machine learning, can identify revenue-generating opportunities in different business processes that include sales and marketing. It also provides solutions for marketing leadership, sales leadership, sales operations, and customer success.

The platform can also accommodate feedback, sales performance analytics, and pipeline reviews to identify if there is any missed opportunity that the business can capitalize on. has raised $100 million, and its headquarter regions include San Francisco Bay Area, West Coast, and the Western US.

  • Cinnamon

Automation is becoming necessary for businesses, especially small ones. Hiring new staff to take care of mundane and repetitive tasks is not a wise choice when the tasks can be automated using machine learning software and products.

Cinnamon is a startup that primarily works on extracting data from unstructured documents.

The startup has developed artificial intelligence products that include Flax Scanner (extracts information from documents), Lapis Engine (recommendation engine), and Scuro Bot (chatbot that understands natural language).

Banking and insurance companies have to go through a lot of paperwork. These industries are steadily adopting these technologies because they are increasingly becoming more accurate with the help of machine learning and artificial intelligence.

Cinnamon was founded in 2012 and is based in Tokyo and Vietnam. It is still an early-stage venture and has received around $17 million in funding.


Machine learning will continue to revolutionize businesses.

Any startups that decide to focus on machine learning as their area of expertise have the potential to snowball. Businesses want quicker and smarter solutions; machine learning happens to provide the means to an end.

Startups that get involved with machine learning have a bright future in front of them. The need for machine learning and artificial intelligence solutions is only going to grow in the future. This makes machine learning a lucrative field for startups to get into and make an impact.

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