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Home » INSIGHTS » Top Machine Learning Startups to Watch – Part 1

Top Machine Learning Startups to Watch – Part 1

Crunchbase today lists more than 8,705 startups and companies that rely on machine learning for their applications, products and services. According to Q4 2018 report by PwC/CB Insights MoneyTree, artificial intelligence-related firms raised $9.3B in 2018, an increase of 72 percent over 2017. And another study found that AI deals increased within a quarter from 104 to 116 deals. According to McKinsey, in marketing and sales, AI and machine learning have the potential to create an additional $2.6 T in value by 2020 and up to $2 T in planning the production and supply chain. Top start-ups offering machine learning services to watch this year:


machine learning

Anodot capitalizes on the innate strengths of machine learning by continuously searching for patterns through the various data sets using constraint-based modelling, which businesses rely on to operate daily. Anodot’s AI platform looks to eliminate blind spots in data and quantify root causes in various data sets, similar to many machine learning startups that capitalize on the ability of the technology to learn continuously. Anodot’s Autonomous Analytics platform uses advanced machine learning techniques to constantly analyze and correlate all business parameters, providing real-time alerts and forecasts in their context, reducing detection and resolution time. Anodot raised a total of $27.5 million in funding. The latest funding came from Redline Capital’s Series B round on Dec. 19, 2017.


Biofourmis is a rapidly growing global digital health tech start-up that combines AI, machine learning, and real-time monitoring to reinvent remote patient monitoring. Their platform can detect personalized patterns that predict the health condition of a patient and can find leading indicators of potential deterioration in health. Their Biovitals platform is one of the most sophisticated personalized data analytics engines based on human physiology, formulating personalized health models, resulting in highly optimized post-acute patient monitoring solutions and predicting patient health deterioration accurately before it occurs. To capture physiological signals and detect anomalies, they use connected devices and bio-sensors. This continuous monitoring platform empowered by AI alerts medical professionals to intervene days prior to a critical event. Their RhythmAnalytics Platform has recently been given FDA clearance for automated cardiac arrhythmia interpretation based on AI. Over six rounds, the startup raised a total of $41.6 million in funding, the latest being from MassMutual Ventures and Sequoia Capital India on May 21, 2019.

Keep watching this space for more.

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