The 10 Hottest Data Science And Machine Learning Startups Of 2020 (So Far)

Businesses looking to bring the rewards of big data analysis to everyday users need ways to prepare and organize data and develop models for analyzing it. Here’s a look at 10 companies that offer ground-breaking data science and machine learning tools that help them do that.

The Scientific Approach

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Before businesses can take advantage of the growing volumes of big data being generated today, data scientists and developers have to prepare and organize the data and develop the underlying machine learning algorithms and predictive models that support the business intelligence applications used by analysts and information workers.

Traditionally that work has been a time-consuming process. But data science, machine learning and artificial intelligence platforms automate much of that work, making it possible for businesses and organizations to leverage their big data assets more quickly for competitive advantage.

Here’s a look at 10 companies in the data science and machine learning arena that solution providers should be aware of.

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Top Executive: Francisco Martin, CEO and co-founder

Headquarters: Corvallis, Ore.

BigML offers a comprehensive, managed machine learning platform for easily building and sharing datasets and models and making highly automated, data-driven decisions. More specifically, the company’s programmable, scalable machine learning platform automates classification, regression, time series forecasting, cluster analysis, anomaly detection, association discovery and topic modeling tasks.

The BigML Preferred Partner Program supports referral partners, sales partners and partners who sell BigML and oversee implementation projects.

Cinnamon AI

Top Executive: Miku Hirano, CEO and Co-Founder

Headquarters: Tokyo, Japan

Cinnamon, a Gartner “Cool Vendor” this year, develops a system that scans unstructured printed and digital documents – everything from PDFs and Word files to handwritten notes and faxes – and extracts the key points. The system, which incorporates AI and machine learning techniques, is designed to reduce business operating costs by eliminating millions of hours of manual input and other repetitive tasks.

Cinnamon also offers a state-of-the-art voice recognition AI system.

In addition to its Tokyo headquarters, Cinnamon has offices in San Mateo, Calif., Taiwan and Vietnam.


Top Executive: Christopher Bergh, CEO

Headquarters: Cambridge, Mass.

Business processes are key to digital transformation initiatives and data flow is key to managing and changing business processes. DataKitchen is a pioneer in the realm of DataOps, the concept of managing data analytics processes like an assembly line instead of the cumbersome, ad hoc processes found within many businesses.

The company’s platform manages the data pipeline through data engineering, data science and business analytics processes. DataOps combines concepts from Agile development, DevOps and statistical process control, among others, in a collaborative workflow.


Top Executive: CEO Ryohei Fujimaki

Headquarters: San Mateo, Calif.

DotData touts its DotData Enterprise machine learning and data science platform as capable of reducing AI and business intelligence projects from months to days. The goal is to make data science processes simple enough that almost anyone, not just data scientists, can benefit from them.

The DotData platform is based on the company’s AutoML 2.0 engine that provides full-cycle automation of data science and machine learning tasks.

DotData raised $23 million in Series A funding in October 2019 and achieved Advanced Technology Partner status in the Amazon Web Services Partner Network in December 2019.


Top Executive: CEO Asaf Somekh

Headquarters: New York and Herzliya, Israel

The Iguazio Data Science Platform automates and accelerates machine learning workflow pipelines, allowing businesses to develop, deploy and manage AI applications at scale that improve business outcomes – what the company calls “MLOps.”

In January Iguazio raised $24 million in funding.


Top Executive: Amnon Drori

Headquarters: Rosh Ha’ayin, Israel

Octopai develops an automated, centralized, metadata management and search engine system that data scientists and business intelligence groups use to discover, govern and track shared metadata.

The software is used to maintain company-wide data consistency and help business analysts find and understand available data. It can also be used for big data governance and compliance tasks where data lineage is key.


Top Executive: Pedro Alves, CEO and Founder

Headquarters: San Mateo, Calif.

The Ople Platform automates big data tasks, such as data preparation and predictive model creation, optimization and deployment, that usually require a data scientist. The software leverages machine learning models that solve complex predictive analytics problems in predictive maintenance, supply chain optimization, financial fraud detection and customer churn.

In March Ople integrated its software with Tableau’s popular business intelligence and data visualization tools, using Tableau’s recently released Analytics Extension API.


Top Executive: John Randles, CEO

Headquarters: Galway, Ireland, and Philadelphia

The Siren Investigative Intelligence Platform uses a data model to drive the discovery of associated data. It combines the capabilities of search, business intelligence dashboards, link analysis and big data logging and alerting.

Siren, a 2020 Gartner “Cool Vendor” in analytics and data science, raised $10 million in Series A funding in November 2019.


Top Executive: Ajay Khanna, CEO

Headquarters: Reston, Va.

Tellius offers a search-driven analytics platform, the Tellius Genius AI Engine, that the company says makes it easier for users to ask questions of, and get actionable insights from, their business big data. The engine incorporates machine learning to uncover patterns and relationships within data while learning from the data itself and from user actions.

The Tellius system’s voice, search and natural language capabilities augment self-service BI and analytics initiatives.


Top Executive: Noah Horton, CEO

Headquarters: Boulder, Colo.

The Unsupervised system uses augmented artificial intelligence, data science and machine learning to help people without deep data science skills analyze huge volumes of complex structured and unstructured data to discover meaningful patterns and insights.

The software works by automating the traditionally manual, time-consuming steps of connecting and aggregating big data, according to a Gartner report that tagged Unsupervised as a “Cool Vendor.”