Forbes： 25 Machine Learning Startups to Watch in 2018

• Crunchbase lists over 5,000 startups who are relying on machine learning for their main and ancillary applications, products and services today.

• 81% of machine learning startups Crunchbase tracks have had two funding rounds or less with seed, angel and early-stage rounds being the most common.

• According to KPMG’s Venture Pulse Report, venture capital (VC) investment in artificial intelligence almost doubled in 2017, attracting $12B compared to $6B in 2016.

• Q2’18 was a second-straight record quarter for total Artificial Intelligence (AI) funding with total investments exceeding $2.3B including eight mega-rounds over $100M according to the latest PwC/CB Insights MoneyTree Report from Q2 2018.

From redefining talent management by evaluating job candidates on innate and emerging strengths by removing conscious and unconscious biases from hiring decisions as eightfold.ai does today to providing a self-service AI platform that is always learning from analytics as Anodot does, machine learning startups are fascinating to track. International Data Corporation (IDC) forecasts that spending on AI and ML will grow from $12B in 2017 to $57.6B by 2021, attaining a 48% Compound Annual Growth Rate (CAGR). Please see the latest roundup of machine learning forecasts and market estimates, 2018 for more market data on machine learnings’ exponential growth.

The National Bureau of Economic Research distributed a study last month from the Stanford Institute For Economic Policy Research titled Some Facts On High Tech Patenting. The study finds that patenting in machine learning has seen exponential growth since 2010 and Microsoft had the greatest number of patents in the 2000 to 2015 timeframe. Using patent analytics from PatentSight and ip-search, IAM published an analysis last month showing Microsoft as the global leader in machine learning patents with 2,075. The study relied on PatentSight’s Patent Asset Index to rank machine learning patent creators and owners, revealing Microsoft and Alphabet are dominating today.

http://www.iam-media.com/blog/Detail.aspx?g=66577171-6786-48a6-b4a3-e2931f1e4146

25 Machine Learning Startups To Watch

Machine learning startups are another source of patents Alphabet, IBM, Intel, GE, Google, Microsoft, Philips, Qualcomm, Samsung, Siemens, Sony and others monitor continually. The following list of 25 machine learning startups are based on an analysis of their ability to attract new customers, current and projected revenue growth, patents’ current value and potential, and position in their chosen markets. Presented below are 25 machine learning startups to watch this year:

1. Anodot–Capitalizes on the innate strengths of machine learning by continually looking for patterns using constraint-based modeling across the diverse data sets businesses are relying on to operate daily. Similar to many machine learning startups that capitalize on the technology’s ability to learn continually, Anodot’s AI platform looks to eliminate blind spots in data and quantify root-causes in diverse data sets. Anodot has approximately 100 customers including Microsoft, Lyft, Waze, Pandora, AppNexus, Wix, and Anodot raised a total of $27.5M in funding over four rounds. The latest funding came from a Series B round on Dec 19, 2017, from Redline Capital. The following screen from their app is an example of how Anodot provides real-time anomaly detection.

2. Cinnamon – Relying on machine learning and AI techniques to automate data extraction from unstructured documents, Cinnamon’s co-founders have extensive experience in recommendation engine design and optimization. They’ve developed several interesting products including Lapis Engine, which combines vectorization of user and product information to deliver accurate recommendations and matching. The company is based in Tokyo and Vietnam and is now expanding to the United States. Cinnamon has raised a total of $10M in funding over five rounds.  The latest funding came from a Series B round on Jun 1, 2018, from SBI Investment.

3. Citrine Informatics– The Citrine Informatics platform ingests and analyzes large-scale technical data sets on materials, chemicals, and devices to streamline R, manufacturing, and supply chain operations for any organization that produces a physical product. Typical system users are scientists and engineers at large manufacturing and materials companies, as well as researchers at universities and government labs. Citrine was recently given the Best AI-based solution for Manufacturing award from AI Breakthrough, an independent organization that recognizes the top companies, technologies, and products in the global Artificial Intelligence (AI) market today. Citrine Informatics raised a total of $15.6M in funding over three rounds. The latest funding came from a Convertible Note round on Apr 19, 2018, from Tencent and B Holdings.

4. CrowdAI – Fascinating startup to track that is using machine learning, computer vision, and human intelligence to maximize the value of aerial, drone and satellite imagery. The startup’s team is from IBM Watson, OpenAI, Google, University of Oxford and UC Berkeley and is backed by Y Combinator. So far CrowdAI has raised a total of $2.1M in funding over two rounds.  The latest funding came from a Seed round on Jan 5, 2017.

5. DataCamp - DataCamp is an interactive learning platform for data science that provides over 100 courses featuring high-quality video, in-browser coding, and gamification. Courses are often authored and presented by analytics, big data, machine learning and AI experts. DataCamp is succeeding in getting companies to subscribe to their training programs to get new hires up to speed. Clients include eBay, BCI, Harvard, and GfK. DataCamp has raised a total of $6.1M in funding over six rounds.  The latest funding came from a Venture Series round on Jul 14, 2017. The following is a screen from the course *Machine Learning with Tree-Based Models in R. *

6. Dataiku - Designed and launched their Data Science Studio platform with the goal of aggregating the process steps needed to transform raw data into data-driven applications that are easy to maintain. The Studios’ workspace is designed to be intuitive, interactive and capable of shortening load-prepare-test-deploy cycles required to create data-driven Dataiku raised a total of $45.7M in funding over four rounds. The latest funding came from a Series B round on Sep 6, 2017, from Battery Ventures.

7. DataRobot–DataRobot is an enterprise machine learning platform designed for broad adoption and usability across the many skill levels in an organization. The platform provides a broad base of algorithms and tools for developing and deploying machine learning and AI projects including libraries of hundreds of open source machine learning algorithms.DataRobot has raised $124.5M in funding over six rounds. The latest funding came from a Series C round on Jul 27, 2017, from New Enterprise Associates, a global venture capital firm investing in technology and healthcare. The following screen from DataRobot Machine Learning’s Automation Platform illustrates how intuitive it is to use. Over 760 million models have been built using DataRobot as of August, 2018.

Source: DataRobot Machine Learning Automation Platform (2 pp., PDF)

1. DataVisor-DataVisor relies on machine learning to discover anomalies in financial data to thwart potential breaches, bank fraud, and other types of criminal activity in the financial services industry. The DataVisor platform is designed to gain insights into fraudulent behavior using unsupervised machine learning to identify attack campaigns before they conduct any damage. DataVisor raised a total of $54.5M in funding over three rounds. The latest funding came from a Series C round on Feb 9, 2018, from Sequoia Capital China.

2. deep6.ai – Deep 6 AI finds patients for clinical trials more efficiently and with greater precision than any existing manual process today. The startup also has a contract with the U.S. intelligence community, which is perhaps the most complex data environment in the world. Since 2016, Deep 6 AI has focused exclusively on healthcare, participating in the Techstars Healthcare Accelerator in partnership with Cedars-Sinai, the Healthbox modified-accelerator program, and Stanford’s StartX Accelerator. Their initial seed round came from The Cedars-Sinai Accelerator and Techstars.

3. Directly- An innovative startup using AI and machine learning to integrate customer service and crowd-sourced expertise and intelligence Directly look to capitalize on the evolving shift to a gig economy. Their platform enables companies to pay experts for responding to questions. AutoDesk is a fan, as can be read in this blog post. Directly raised a total of $35.8M in funding over five rounds from Costanoa Ventures, Microsoft Ventures, and True Ventures. The latest funding came from a Series B round on Apr 10, 2018, from Northgate Capital.

4. DrawBridge-Creating cross-device, people-based identity management solutions using AI and machine learning to secure the perimeters of digital businesses, DrawBridge is known for the combining data analytics and integration. Drawbridge raised a total of $68.7M in funding over six rounds. The latest funding came from a Venture - Series round on Aug 20, 2018 from Sequoia Capital, Northgate Capital and Kleiner Perkins.

5. eightfold.ai -Strip away the hype swirling around AI in talent management and what’s left is the urgent, unmet needs companies have for greater contextual intelligence and knowledge about every phase of talent management. Using advanced AI and machine learning techniques, a company founded by former Google and Facebook AI Scientists is showing potential in meeting these challenges. Founders Ashutosh Garg and Varun Kacholia have over 6000+ research citations and 80+ search and personalization patents. What makes Eightfold.ai noteworthy is that it’s the first AI-based Talent Intelligence Platform that combines analysis of publicly available data, internal data repositories, Human Capital Resource Management (HRM) systems, ATS tools and spreadsheets then creates ontologies based on organization-specific success criteria. Each ontology, or area of talent management interest, is customizable for further queries using the app’s intuitive user interface. Eightfold raised a total of $23.75M in funding over two rounds. The latest funding came from a Series B round on Apr 17, 2018, from Lightspeed Venture Partners and Foundation Capital. The following is an overview of the Eightfold Talent Intelligence Platform.

6. First.-First is a software company that uses artificial and predictive intelligence on when and why people move to predict sales and marketing. It brings predictive marketing to real estate, fundamentally changing how service providers find their next customer. They discover when and why people will buy or sell a house so that they can connect realtors with new clients at the perfect time. Thus, the company predicts who will sell by tracking 700+ signals across 214M people nationwide. First raised a total of $7.35M in funding over three rounds. The latest funding came from a Series A round on May 22, 2018, from Nine Four Ventures, MATH Venture Partners, and others.

7. Freenome-Freenome is an AI-based genomics company on a mission to provide people with the tools they need to detect, treat, and ultimately prevent their diseases. By applying advanced machine learning techniques to recent breakthroughs in genomic science, Freenome is developing noninvasive blood tests to detect early-stage cancer and improve precision oncology treatments for patients everywhere. Freenome raised a total of $77.5M in funding over three rounds. The latest funding came from a Series A round on Aug 28, 2017, from Section 32.

8. H2O.ai - H2O.ai provides an open source machine learning platform that simplifies the development of data-driven smart applications. Data scientists and developers are using the H2O.ai platform to create, test and scale algorithms that are the foundation of applications. H2O.ai apps are being used today to predict fraud, customer churn and solve many other complex problems their customers have. Key clients include Cisco, PayPal, and Progressive. H2O.ai raised a total of $73,600,000 in funding over five rounds. The latest funding came from a Series C round on Nov 30, 2017 lead by Nvidia and Wells Fargo.

9. Innovaccer–Innovaccer develops AI- and machine learning-based systems for healthcare organizations, enabling them to integrate complex data across multiple distributed sources and provide valuable insights to healthcare professionals. Innovaccer’s Datashop application includes proprietary modeling algorithms that normalize data and links data across multiple disparate data sources. Innovaccer also provides solutions for care management, referral management, and patient engagement and has raised a total of $43.1M in funding over three rounds. The latest funding came from a Series B round on May 10, 2018, from WestBridge Capital.

10. IronScales- An innovative startup using machine learning to develop an employee-based intrusion prevention system with an automated phishing-mitigation response, IronScales allows enterprises to protect themselves from criminals attempting to deceive employees into revealing sensitive information such as usernames and passwords so they can then install spyware, remote-access Trojan horse attacks or ransomware. The startup raised a total of $8M in funding over two rounds. The latest funding came from a Series A round on Dec 5, 2017, from K1 Investment Management.

11. LeadGenius–LeadGenius is a leader in the evolving AI and machine learning-based areas of marketing automation. The company has created and sells an end-to-end sales solution that provides companies with a way to generate, qualify, deliver, and convert leads in addition to helping launch and excel at Account Based Marketing (ABM) strategies. It helps sales teams grow and scale across all levels of the sales process. LeadGenius was launched by Anand Kulkarni, Prayag Narula, and Dave Rolnitzky in 2011. LeadGenius raised a total of $19M in funding over five rounds. The latest funding came from a Series B round on May 14, 2018, from Sierra Ventures.

12. Lemonade- Lemonade is a licensed insurance carrier that offers homeowners and renters insurance powered by artificial intelligence and behavioral economics. By replacing brokers and bureaucracy with bots and machine learning, Lemonade drastically reduces paperwork and delays inherent in manual insurance processes. And as a Certified B-Corp, where underwriting profits go to nonprofits, Lemonade is remaking insurance as a social good. Lemonade raised a total of $180M in funding over five rounds. The latest funding came from a Series C round on Dec 19, 2017, with SoftBank

13. LogiNext–LogiNext is a fascinating startup using AI and machine learning to bring greater innovation to field workforce and logistics optimization. The startup offers field workforce optimization, real-time tracking, route optimization, resource allocation automation and on-demand management to more than 250 enterprise clients. They also have developed apps for last mile management, field workforce management, long-haul tracking and management, On-Demand and Reverse Logistics Management. LogiNext raised a total of $10.6M in funding over two rounds.

14. Obsidian Security-Led by former founding team members of Cylance and Carbon Black, Obsidian Security is a Southern California technology company living at the intersection of cybersecurity, artificial intelligence, and hybrid-cloud environments. Their vision is to revolutionize how organizations use data science and security technology to combat cyber threats across hybrid-cloud environments. Backed by Greylock Partners, Obsidian Security is based in Newport Beach, CA. The company has raised a total of $9.5M in funding in its only round. The latest funding came from a Series A round on Jun 8, 2017.

15. Quantexa-Quantexa is taking a unique approach to using AI and machine learning to decipher and solve a wide variety of complex problems, ranging from thwarting financial crimes, reducing credit risk and eradicating money laundering operations. Shell Oil is relying on their solution to reduce churn with enterprise accounts. The startup has generated £5M ($6.42M) in revenue and 400% year-over-year growth. The company has raised a total of $23.3M in funding over two rounds. The latest funding came from a Series B round on Aug 2, 2018 form Dawn Capital.

16. Segmentify –Segmentify’s vision is to create a better online shopping experience personalized for each visitor and increase the conversion rates for online retailers. The startup does this by creating a unique online shopping experience that is relevant to each visitor by utilizing advanced machine learning technology. Segmentify raised a total of €1,015,000 ($1.1M) in funding over three rounds. The latest funding came from a Seed round on Nov 13, 2017, by ACT Venture Partners.

17. Showpad – Using AI, advanced analytics and machine learning to recommend which content resonates with prospects based on their stage in a buying cycle, Showpad brings greater insight and intelligence into sales enablement. The suite of applications can also provide sales managers with insights into the behaviors of the highest performing sales representatives and replicate the results across entire teams. Customers rate Showpad high on usability, intuitiveness and analytics insights that weren’t available on standard sales enablement-based content management systems. Showpad raised a total of $89.5M in funding over five rounds. The latest funding came from a Series C round on Jan 24, 2018, from Insight Venture Partners.

18. Tamr - Following the success of initial research at MIT Computer Science and Information Lab (CSAIL), the Tamr team began building a commercial-grade solution designed to tackle the challenge of connecting and enriching diverse data at scale using machine learning. Today TAMR can reduce the time required for data unification projects by 90% using advanced analytics including machine learning algorithms. Amgen, GlaxoSmithKline, GE, HP, Roche, Toyota, and others are current clients. Tamr has raised a total of $59.2M in funding over four rounds. The latest funding came from a Series B round on Jul 11, 2018, from SBI Investment.

Sources:

KPMG, Venture Pulse Q4 2017 Global analysis of venture funding (PDF, 105 pp., no opt-in)

National Bureau of Economic Research Some Facts of High-Tech Patenting

By Michael Webb, Nick Short, Nicholas Bloom, Josh Lerner NBER Working Paper No. 24793 Issued in July 2018

PwC / CB Insights MoneyTree Report Q2 2018 (PDF, 75 pp., no opt-in)

Roundup Of Machine Learning Forecasts And Market Estimates, 2018, Forbes, February 18, 2018