5 Machine Learning Startups to Watch in 2021

By Adriaan Brits | Friday, 01 October 2021 | Feature, Startup, Tech

Although machine learning sounds like something from a dystopian sci-fi movie, it’s actually much less threatening — and potentially more useful. According to IBM, machine learning is a branch of artificial intelligence (AI) and computer science that uses data and algorithms to imitate the way that humans learn. Through this process, computers can gradually improve their productivity and accuracy in all sorts of tasks over time, rather than rotely following instructions that software developers program into them.

Artificial intelligence concept.

According to Grand View Research, the global market for machine learning was worth $6.9 billion in 2018 and is expected to grow by 43% between 2019 and 2025. Machine learning is transforming the way people do all sorts of things, from optimizing supply chains to launching digital products and services to improving the customer experience. For example, machine learning is being used to predict customers’ behavior, make advertising campaigns more effective, improve the process of loan approvals, optimize assets and document management, and enhance online security. The machine learning market includes hardware, software, and services. The hardware segment is projected to grow the fastest, due in part to the development of ever more powerful computer chips.

The machine learning industry has spawned many startups that are leading the charge in this exciting field. Here are a few of them.

Avora ($9.7 Million in Total Funding)

London-based Avora uses augmented analytics to help companies analyze data as easily as conducting a web search. Even people who don’t consider themselves technically inclined can use its easy-to-navigate interface, which answers queries in plain language, detects potentially important data anomalies, performs root-cause analyses in the background to identify factors that may cause unexpected changes to important business metrics, and provides a more accurate forecast. Reports are easily shareable, and the time for data preparation and discovery is cut by more than half compared to traditional methods of data analysis. The company has customers in a variety of industries, including advertising, retail, media, financial services, and supply chain management. 

Avora was named the UK’s 42nd fastest growing technology company at Deloitte Fast 50 Awards, which rank the country’s 50 fastest-growing technology companies based on revenue growth over the previous four years.

Zest AI ($250 Million in Total funding)

Zest AI, based in Los Angeles, seeks to help lenders perform one of their most difficult — and yet most crucial — tasks: identifying which borrowers are worth the risk and which are not. The company has created a machine learning platform that allows lenders to analyze large amounts of credit and other relevant data to make safer loans, especially to people like millennials who present a heightened credit risk. This method allows lenders to reach borrowers who might otherwise have been deemed too risky because of their short or non-existent credit histories. Lenders can also use the platform to help comply with financial regulations and measure the business impact of various loans. 

“The difficulty financial institutions face underwriting millennials is their limited credit histories – they’re a classic example of thin-file or no-file borrowers,” Douglas Merrill, founder and CEO of ZestFinance, told Businesswire. “Traditional underwriting works well when evaluating borrowers with long credit histories, but when there is limited data, it can’t differentiate between creditworthy and high-risk applicants. Machine learning fills those gaps by analyzing a vastly broader set of data.” Zest AI says its platform is both powerful and easy to use. Among other recent developments, the company announced an $18 million capital injection led by investors VyStar Credit Union and First National Bank of Omaha, along with returning investor Northgate Capital.

Particle ($75.8 Million in Total Funding)

San Francisco-based Particle has developed a platform for managing Internet of Things (IoT) devices. More and more gadgets are being connected to the internet, and successfully and securely integrating them is a significant challenge. Using Particle, companies large and small can build and manage IoT systems and networks. Particle’s end-to-end platform is designed to help companies program their machines and products to make them more interconnected and intelligent. Companies can use the platform to (among other things) remotely monitor IoT devices, send commands, and check device variables, and track the location of business-critical assets.

“Over the last seven years we’ve seen a wide range of businesses embrace IoT, especially those driving innovation in traditional industries,” CEO Zach Supalla told Venture Beat. “More and more of our customers are in old-fashioned, even unglamorous, businesses like stormwater management, industrial equipment, shipping, or monitoring any number of compressors, pumps, and valves. These businesses are diverse, but the common thread is that they need to monitor and control mission-critical machines, and we see it as our mission to help bring their machines, vehicles, and devices into the 21st century.” The company has more than 200,000 developers and engineers in more than 170 countries.

DataVisor ($54.5 Million in Total Funding)

Another California firm, DataVisor, uses machine learning and AI to help organizations detect patterns that may indicate fraud. According to the company, “reactive” approaches to fraud won’t do in today’s fast-paced, interconnected world, especially with so much mischief being perpetrated by automated bots. DataVisor says it offers the only comprehensive fraud prevention solution that proactively detects fraud before it occurs. Leveraging its global intelligence network of more than 4.2 billion users along with advanced analytics, DataVisor can help businesses in a variety of industries protect their reputations and finances.

The company is bullish on its future. “Demand for fraud and risk management continues to be strong, as digital channels go through the next wave of growth,” Co-founder and CEO Yinglian Xie said in a press release. “As companies expand their offerings to incorporate digital technologies and channels, the need to protect good customers becomes increasingly critical.” DataVisor was named a Gartner Cool Vendor in Identity and Access Management and Fraud Detection, as well as a leader in the IDC MarketScape: Worldwide Enterprise Fraud Management in Banking 2020 Vendor Assessment.

ClosedLoop.ai ($14 Million in Total Funding)

ClosedLoop.ai calls itself “healthcare’s data science platform.” The firm combines an intuitive end-to-end machine learning platform with a comprehensive library of healthcare-specific features and model templates. The platform includes predictive and prescriptive models that healthcare providers can customize for the specific populations they serve. Providers can use ClosedLoop’s Explainable AI to improve care, predict chronic diseases, predict the risks of various interventions and treatments, streamline patient experiences, reduce no-show appointments, improve operational efficiency, and increase revenue.

Among other recent accomplishments, the company won the AI Health Outcomes Challenge, a contest led by the Centers for Medicare & Medicaid Services to make accurate health predictions for individual patients that their healthcare providers could act upon. The company also announced a new relationship with Palm Beach Accountable Care Organization, one of the nation’s leading and most successful physician-led accountable care organizations in the Medicare Shared Savings Program. ClosedLoop.ai says its AI platform benefits more than 3 million patients every day in major healthcare organizations around the US.

About the Author

Headshot of Adriaan Brits

An analyst of global affairs, Adriaan has an MSC from Oxford, with diverse interests in the digital economy, entertainment, and business. He is a specialist trainer in advanced analytics and media.

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