Healthcare Analytics Market, Part 2

Part
01
of one
Part
01

Healthcare Analytics - ClosedLoop Competitive Analysis, Part 2

DataRobot automates machine learning to help healthcare companies identify patients with a high likelihood of a particular disease before they seek care.

DataRobot

Description
  • DataRobot, Inc. provides Internet-based services that develop and markets Internet software to collect and connect predictive models for data science, to provide statistical models to customers.
  • DataRobot automates machine learning to help healthcare companies identify patients with a high likelihood of a particular disease before they seek care.
  • DataRobot platform can work with healthcare companies to turn the troves of data found in electronic medical records, diagnostic data, and medical claims information into cutting edge insights and predictions that optimize business processes.
Funding History
  • DataRobot has raised a total of $430.6 million in funding over 7 rounds.
  • 2013: Datarobot raised $118k and $3.3 million from Seed round funding.
  • 2014: Raised $21 million in Series A investment from New Enterprise Associates.
  • 2016: Raised $33 million in Series B investment from New Enterprise Associates.
  • 2017: raised $67.2 million in Series C investment from venture capital firm New Enterprise Associates.
  • 2018: Raised $100 million in Series D investment from Meritech Capital Partners and Sapphire Ventures.
  • 2019: Raised $206 million in Series E investment from Sapphire Ventures.
Revenue
  • The estimated annual revenue of the company is $37 million.
  • Overall the company has more than 400 customers.
  • Aegon, Australian Red Cross Blood Service, BlueCross BlueShield, Humana are some customers of Datarobot.
  • Datarobot has about 701-800 employees.

Amazon SageMaker

Description
  • In 2017, Amazon Web Services introduced the Amazon SageMaker platform.
  • Amazon SageMaker is a cloud machine-learning platform that enables developers to create, train, and deploy machine-learning models in the cloud.
  • Amazon SageMaker platform provides health systems with scalable and powerful ways to process large datasets and the Comprehend Medical tool delves into unstructured data.
Funding History
  • Amazon SageMaker has not received any funding, however, the parent company Amazon has received 2 funding rounds.
  • Amazon received $8 million in Series A funding from Kleiner Perkins in 1996 and $100 million funding in 2001.
Revenue
  • Amazon Web Services which has an Amazon SageMaker platform has an estimated revenue of $20 billion.
  • Thousands of customers are using Amazon Web Services- Amazon SageMaker platform.
  • GE Healthcare, ProQuest, Celgene, Thomson Reuters, Atlas Van Lines, Tinder, Edmunds, Zendesk, Regit, are some customers of Amazon Sagemaker.
  • There is no information on the estimated number of employees of Amazon SageMaker, however the parent company Amazon employed approximately 566,000 full-time and part-time employees as of December 31, 2017.
  • Amazon Web Services which includes Amazon SageMaker platform has more than 10,000 employees.

Your Research Team Applied The Following Strategy

Information on the funding history, revenue, estimated number of employees, number of customers of DataRobot and Amazon Sagemaker in the healthcare segment is not available.

Our first strategy was to look for information on the company website of Datarobot and Amazon Sagemaker. Our idea here was to review the company websites, press releases, annual reports to find the required information. This strategy worked to an extent as we were able to find information on the funding details, customer names of these companies. However, there was no information on the funding history, revenue, number of employees, on the healthcare segment exclusively. We had thought that this strategy may work as companies publish information about its organization stats on its website, annual reports, however, since these companies provide services to other industries including healthcare, there was no separate information found. Datarobot being a private company does not publish annual reports, and Amazon Sagemaker which is a part of Amazon company (public company) has also not published this information exclusively only for Amazon Sagemaker.

Our second strategy was to search for information on health publication sites like healthcareitnews, Healthline, medicalnewstoday among others. The idea here was to find publications on the healthcare industry that would include commentaries by industry experts, company spokespersons that could be used to devise such information. However, no such information was found. At most, we could find details about the company’s services in the healthcare segment, we had thought that this strategy may work as sites like these publish information on emerging technologies, tools, in the health industry and may have published this information. We then looked for interviews of the company employees like executives from the healthcare segment on sites like business insider, and CNBC among others. Our idea here was to see if any of the industry executives have quoted stats about the company in their interviews, however, there was no such information found.

Our third strategy was to look for information on company database sites like Crunchbase, Pitchbook, Hoovers, zoominfo among others. Our idea here was to see if any of the database sites have published information on these companies along with stats for the healthcare segment. This strategy did not work as the database found was for the overall company and not exclusive for the healthcare segment. For Amazon sagemaker, the database found was of the parent organization and not of the business unit. We had thought that this strategy may work as database sites publish information on the company overview like the number of employees, revenues, and would have published this information.
Sources
Sources

Quotes
  • "Our mission for healthcare organizations is to use AI to improve operations, lower costs, and deliver the best care for patients. DataRobot can work with you to turn the troves of data found in electronic medical records, diagnostic data, and medical claims information into cutting edge insights and predictions that optimize business processes across your organization."
Quotes
  • "Amazon SageMaker is a fully-managed service that covers the entire machine learning workflow to label and prepare your data, choose an algorithm, train the model, tune and optimize it for deployment, make predictions, and take action. Your "
Quotes
  • "Amazon's new machine learning offerings promise wide range of healthcare applications Its Elastic Inference and SageMaker platforms provide health systems with scalable and powerful ways to process large datasets, while the new Comprehend Medical tool delves into unstructured data."
Quotes
  • "AWS – It’s exciting to see Amazon Web Services, a $20 billion revenue run rate business, accelerate its already healthy growth. "
  • "In 2017, AWS announced more than 1,400 significant services and features, including Amazon SageMaker, which radically changes the accessibility and ease of use for everyday developers to build sophisticated machine learning models. Tens of thousands of customers are also using a broad range of AWS machine learning services, with active users increasing more than 250 percent in the last year, spurred by the broad adoption of Amazon SageMaker"