Artificial Intelligence Q1 Update in 15 Visuals

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We at Venture Scanner are tracking 957 Artificial Intelligence companies across 13 categories, with a combined funding amount of $4.8 Billion. The 15 visuals below summarize the current state of Artificial Intelligence.

1. Artificial Intelligence Market Overview

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We organize Artificial Intelligence into the 13 categories listed below:

Deep Learning/Machine Learning (General): Companies that build computer algorithms that operate based on their learnings from existing data. Examples include predictive data models and software platforms that analyze behavioral data.

Deep Learning/Machine Learning (Applications): Companies that utilize computer algorithms that operate based on existing data in vertically specific use cases. Examples include using machine learning technology to detect banking fraud or to identify the top retail leads.

Natural Language Processing (General): Companies that build algorithms that process human language input and convert it into understandable representations. Examples include automated narrative generation and mining text into data.

Natural Language Processing (Speech Recognition): Companies that process sound clips of human speech, identify the exact words, and derive meaning from them. Examples include software that detects voice commands and translates them into actionable data.

Computer Vision/Image Recognition (General): Companies that build technology that process and analyze images to derive information and recognize objects from them. Examples include visual search platforms and image tagging APIs for developers.

Computer Vision/Image Recognition (Applications): Companies that utilize technology that process images in vertically specific use cases. Examples include software that recognizes faces or enables one to search for a retail item by taking a picture.

Gesture Control: Companies that enable one to interact and communicate with computers through their gestures. Examples include software that enables one to control video game avatars through body motion, or to operate computers and television through hand gestures alone.

Virtual Personal Assistants: Software agents that perform everyday tasks and services for an individual based on feedback and commands. Examples include customer service agents on websites and personal assistant apps that help one with managing calendar events, etc.

Smart Robots: Robots that can learn from their experience and act autonomously based on the conditions of their environment. Examples include home robots that could react to people’s emotions in their interactions and retail robots that help customers find items in stores.

Recommendation Engines and Collaborative Filtering: Software that predicts the preferences and interests of users for items such as movies or restaurants, and delivers personalized recommendations to them. Examples include music recommendation apps and restaurant recommendation websites that deliver their recommendations based on one’s past selections.

Context Aware Computing: Software that automatically becomes aware of its environment and its context of use, such as location, orientation, lighting and adapts its behavior accordingly. Examples include apps that light up when detecting darkness in the environment.

Speech to Speech Translation: Software which recognizes and translates human speech in one language into another language automatically and instantly. Examples include software that translates video chats and webinars into multiple languages automatically and in real-time.

Video Automatic Content Recognition: Software that compares a sampling of video content with a source content file to identify the content through its unique characteristics. Examples include software that detects copyrighted material in user-uploaded videos by comparing them against copyrighted material.

2. Company Count by Artificial Intelligence Category

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The above graph summarizes the number of companies in each Artificial Intelligence category to show which categories are dominating the current market. The Machine Learning (Applications) category is leading the way with 263 companies, followed by the Natural Language Processing category with 154 companies.

3. Funding by Artificial Intelligence Category

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The above graph summarizes the total amount of funding in each Artificial Intelligence category. The Machine Learning (Applications) category is leading the market with over $2B in total funding, which is 3X the total funding of the second highest category, Natural Language Processing with $662M.

4. Venture Investing in Artificial Intelligence

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The above graph compares the total venture funding in each Artificial Intelligence category to the number of companies in the category. The Machine Learning (Applications) category is leading in both stats with over $2B in funding and 263 companies. Natural Language Processing is the runner-up in both stats with $662M in funding and 154 companies.

5. Artificial Intelligence Total Funding by Year

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The above graph summarizes the total funding raised by Artificial Intelligence companies each year. 2015 was the best year in Artificial Intelligence funding with almost $1.2B raised, with 2014 in the second place with a total of $1B raised.

6. Average Funding by Artificial Intelligence Category

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The above graph summarizes the average company funding in each Artificial Intelligence category. The Machine Learning (Applications) category leads the market with $17M in funding per company, followed by the Smart Robots and Gesture Control categories each with about $14M in funding per company.

7. Average Age by Artificial Intelligence Category

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The above graph summarizes the average age of companies in each Artificial Intelligence category. Speech to Speech Translation ranks as the most mature Artificial Intelligence category with an average age of 13 years per company, which is more than 1.5X the average age of the three runner-up categories (Gesture Control, Video Content Recognition, and Speech Recognition, each with an average age of about 8 years per company).

8. Median Age by Artificial Intelligence Category

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The above graph summarizes the median age of companies in each Artificial Intelligence category. Video Content Recognition ranks as the most mature Artificial Intelligence category with a median age of 7.8 years per company, followed by Speech to Speech Translation with a median age of 7.2 years per company.

9. Artificial Intelligence Company Count by Country

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The above map shows the number of Artificial Intelligence companies located in different countries. The United States ranks as the top country with 499 Artificial Intelligence companies, with the United Kingdom at a distant second with 60.

10. Artificial Intelligence VC Funding by Country

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The above map shows the amount of Artificial Intelligence venture capital funding in different countries. The United States has the most Artificial Intelligence VC funding at $4.2B, followed by Switzerland at $234M.

11. Artificial Intelligence Companies Founded by Year

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The above graph summarizes the number of Artificial Intelligence companies founded in a certain year. 2013 ranks as the top year with 118 Artificial Intelligence companies founded, followed by 2012 with 103 companies founded.

12. Artificial Intelligence Funding by Vintage Year

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The above graph summarizes the total amount of funding raised by the Artificial Intelligence companies founded in a certain year. Artificial Intelligence companies founded in 2010 have raised the most funding at $566M, with those founded in 2012 at a close second with $556M.

13. Artificial Intelligence Headcount Distribution

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The above graph summarizes the percentage of Artificial Intelligence companies with a certain employee headcount range. Companies with 1–50 employees make up almost 90% of the market.

14. Number of Artificial Intelligence Investments by Selected Investors

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The above graph summarizes the total number of investment rounds Artificial Intelligence investors participated in. Accel outperform all of its peers, having made 23 investments into Artificial Intelligence companies. New Enterprise Associates is the runner-up with 18 investments.

15. Number of Artificial Intelligence Companies Backed by Selected Investors

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The above graph summarizes the number of unique Artificial Intelligence companies funded by selected investors. Accel takes the top spot by having invested in a total of 20 unique Artificial Intelligence companies, which is almost 1.5X the number of companies invested by the runner-up, Intel Capital (14 companies).

As Artificial Intelligence continues to grow, so too will its moving parts. We hope this post provides some big picture clarity on this booming industry.

Note: If you missed it, you can also read our FinTech Q1 Update in 15 Visuals.

Venture Scanner is your platform for startup landscapes, data, and research. If you would like access to the full Artificial Intelligence landscape and dataset, visit www.venturescanner.com/artificial-intelligence or reach out to [email protected].

Introducing the Energy Technology Startup Ecosystem

We cover many emerging sectors in the startup ecosystem. Today we would like to introduce our coverage of the Energy Technology startup ecosystem. As of now, we are tracking 570 Energy Technology companies in 12 categories, with a total of $26 Billion in funding. To see the full list Energy Technology companies, contact us at [email protected]

Energy Technology Visual Map

Solar Energy: Companies that generate power by converting sunlight into electricity. Examples include solar panel manufacturers, designers, installers, and monitoring solutions.

Wind Energy: Companies that generate power using air flow. Examples includes wind turbine manufacturers, designers, installers, and monitoring solutions.

Geothermal Energy: Companies that use geothermal power to generate electricity. Examples include geothermal energy development, design, and monitoring.

Hydropower Energy: Companies that generate power from the energy of moving water. Examples include wave energy converters, run-of-the-river systems, as well as project management and monitoring solutions.

Bioenergy: Companies that generate energy from biomass. Examples include bioenergy development, research, and monitoring.

Energy Production By-Product Management: Solutions that reduce waste from energy production as well as solutions that recover energy from the production of waste. Examples include treatment of waste water from fracking, treatment of nuclear waste, and conversion of non-recyclable waste into energy.

Energy Storage: New innovations in storing energy to level peak energy demand and store excess renewable energy. Examples include battery solutions, as well as storage brokers and dealers.

Energy Infrastructure: Enabling technologies in the production of energy. Examples include smart metering, energy monitoring/data analytics, and smart grid optimization.

Traditional Energy Enhancements: Technologies that improve the effectiveness and sustainability of traditional energy sources. Examples include solutions that make fossil fuel emissions cleaner and solutions that improve the efficiency of extraction.

Carbon Management: Technologies that aim to reduce carbon dioxide and other greenhouse emissions. Examples include solutions that capture, sequester, and store carbon emissions, carbon emission data analytics, and carbon emission recycling.

Fuel Cell Technology: Companies that generate power by using hydrogen and oxygen for fuel. Examples include fuel cell development, research, and monitoring.

Consumer Energy Efficiency Tools: B2C tools that helps consumers become more energy efficient. Examples include automated solutions to manage home energy use, energy efficient appliances, and home energy data analytics.

Venture Scanner is your platform for startup landscapes, data, and research. If you would like access to the full Energy Technology landscape and dataset, visit www.venturescanner.com or reach out to [email protected].

 

FinTech Q1 Update in 15 Visuals

NOTE: Our blog has moved! Please visit our new blog at https://www.venturescanner.com/blog to read up on our latest content.

We at Venture Scanner are tracking 1,379 FinTech companies across 16 categories, with a combined funding amount of $33 Billion. The 15 visuals below summarize the current state of Financial Technology.

1. Financial Technology Market Overview

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We organize Financial Technology into the 16 categories listed below:

Consumer Lending: New ways for consumers to obtain personal loans and have their credit risk assessed. Examples includes peer-to-peer lending, micro-financing, big data analytics, and consumer credit scoring services.

Business Lending: New ways for companies to raise debt financing and have their credit risk assessed. Examples Include peer-to-peer lending platforms, asset-based lines of credit, micro-financing, and big data risk analytics.

Personal Finance: New ways for consumers to manage their personal finances. Examples include tools for tracking expenses, managing a budget, addressing wrongful credit card charges, and optimizing credit card rewards.

Consumer Payments: Payment companies centered around issuers and consumers. Examples include mobile wallets, credit card aggregators, prepaid card innovations, and peer-to-peer payments.

Payments Backend and Infrastructure: Payment companies centered around acquirers and the infrastructure enabling payments. Examples include payment solutions for e-commerce merchants, online payment gateways, ACH, direct deposits, and payment back-ends for mobile apps.

Point of Sale Payments: Payment companies centered around acquirers, providing physical payment solutions for brick-and-mortar businesses and organizations. Examples include mobile point-of-sales (POS) systems and POS innovations (e.g. QR code, palm scanners).

Equity Financing: News ways for private companies to raise capital in exchange for equity and for investors to participate in private securities markets. Examples include crowdsourcing platforms and secondary market solutions.

Retail Investing: New ways for consumers to invest in various securities. Examples include theme-based investments, crowdsourced investment expertise, unbiased algorithmic investment advice, and investment social networks.

Small and Medium Business Tools: Tools that help small and medium sized businesses manage their finances. Examples include tools for taxes, payroll, invoicing, and accounting.

Institutional Investing: New ways for wealth managers, hedge fund managers, and professional traders to manage their portfolios and optimize returns. Examples include tools for stock sentiment analysis, alternative investment platforms, and algorithmic trading tools.

Banking Infrastructure: Solutions that improve the operations of financial institutions. Examples include API integration with banks, white-label mobile solutions, and big-data analytics.

Financial Transaction Security: New ways for companies to secure transactions, authenticate users, and prevent fraud. Examples include identify verification, big data analytics, and fraud detection algorithms.

Crowdfunding: New ways for companies to raise non-equity and non-debt financing. Examples include crowdfunding platforms for products, social causes, and creative projects.

Consumer and Commercial Banking: New ways for consumers and SMBs to interface with banking services. Examples include Internet-only banking services and virtual credit cards.

International Money Transfer (Remittances): Companies that allow businesses and individuals to send money abroad easily and cheaply. Examples include digital-only remittances, mobile top-off services, and gift cards.

Financial Research and Data: Information services that enable investors to make better investment decisions. Examples include news, research, and data sources.

2. Company Count by FinTech Category

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The above graph summarizes the number of companies in each FinTech category to show which categories are dominating the current market. The Consumer Lending category is leading the way with 198 companies, followed by the Personal Finance and Business Lending categories, each with 148 companies.

3. Funding by FinTech Category

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The above graph summarizes the total amount of funding in each FinTech category. The Consumer Lending category is leading the market with over $12B in total funding, which is 1.5X the total funding of the second highest category, Business Lending.

4. Venture Investing in FinTech

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The above graph compares the total venture funding in each FinTech category to the number of companies in the category. The Consumer Lending category is leading in both stats with over $12B in funding and 198 companies. Business Lending is the runner-up with $8B funding, and has the second-highest company count along with Personal Finance (148).

5. FinTech Total Funding by Year

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The above graph summarizes the total funding raised by FinTech companies each year. 2015 was the best year in FinTech funding with a total of $12B raised, which is 1.5X the amount of funding raised in 2014 ($8B).

6. Average Funding by FinTech Category

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The above graph summarizes the average company funding in each FinTech category. The Consumer Lending category leads the market with $100M funding per company, followed by the Business Lending category at a close second with $92M funding per company.

7. Average Age by FinTech Category

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The above graph summarizes the average age of companies in each FinTech category. Banking Infrastructure ranks as the most mature FinTech category with an average age of 8 years per company, which is twice the average age as the least mature category, Equity Financing (4 years per company).

8. Median Age by FinTech Category

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The above graph summarizes the median age of companies in each FinTech category. Banking Infrastructure ranks as the most mature FinTech category with a median age of 7 years per company, followed by Financial Security and Business Payments, each with a median age of 6 years per company.

9. FinTech Company Count by Country

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The above map shows the number of FinTech companies located in different countries. The United States ranks as the top country with 756 FinTech companies, with the United Kingdom at a distant second with 161.

10. FinTech VC Funding by Country

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The above map shows the amount of FinTech venture capital funding in different countries. The United States has the most FinTech VC funding at $13B, followed by the United Kingdom at $6B.

11. FinTech Companies Founded by Year

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The above graph summarizes the number of FinTech companies founded in a certain year. 2012 ranks as the top year with 186 FinTech companies founded, followed by 2013 with 158 companies founded.

12. FinTech Funding by Vintage Year

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The above graph summarizes the total amount of funding raised by the FinTech companies founded in a certain year. FinTech companies founded in 2011 have raised the most funding at $6.2B, followed by those founded in 2012 with $4.6B funding to date.

13. FinTech Headcount Distribution

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The above graph summarizes the percentage of FinTech companies with a certain employee headcount range. Companies with 1–50 employees make up 73% of the market.

14. Number of FinTech Investments by Selected Investors

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The above graph summarizes the total number of investment rounds FinTech investors participated in. Accel outperform all of its peers, having made 79 investments into FinTech companies. This is almost 2X the number of investments made by the runner-up Sequoia Capital with 45 investments.

15. Number of FinTech Companies Backed by Selected Investors

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The above graph summarizes the number of unique FinTech companies funded by selected investors. Accel takes the top spot by having invested in a total of 54 unique FinTech companies, which is almost 1.5X the number of companies invested by the runner-up, Y Combinator (37 companies).

As FinTech continues to grow, so too will its moving parts. We hope this post provides some big picture clarity on this booming industry.

Venture Scanner is your platform for startup landscapes, data, and research. If you would like access to the full FinTech landscape and dataset, visit www.venturescanner.com/financial-technology or reach out to [email protected].

The State of Health Technology in Six Visuals

We cover many emerging markets in the startup ecosystem. We previously published posts that summarized Financial Technology, Internet of ThingsBitcoin, MarTech, Artificial Intelligence, Retail Technology, and Connected Transportation in six visuals. This week, we do the same with Health Technology. At this time, we are tracking 863 Health Technology companies across 23 categories, with a combined funding amount of $15.5B. To see all of our Health Tech related posts, click here!

The six Health Technology visuals below help make sense of this dynamic market:

  1. Market Overview: Breakdown of Health Technology into categories.
  2. Number of Companies Per Category: Bar graph summarizing the number of companies in each Health Technology category.
  3. Average Funding By Category: Bar graph summarizing average company funding per Health Technology category.
  4. Venture Funding in Health Technology: Graph comparing total venture funding in Health Technology to the number of companies in each category.
  5. Global Breakdown of Health Technology: Heat map indicating where Health Technology companies exist.
  6. Median Age of Health Technology Categories: Bar graph of each Health Technology category by median age.

This sector covers companies that combine IT with healthcare to enhance well-being. This includes digital technologies and services such as mobile connectivity, biometric sensors, cloud computing, social networking, robotics, etc. that are affecting all fronts of healthcare such as hospital management, doctor-patient relationships, peer-to-peer support groups, and personal fitness.

Below you’ll find our Health Tech sector map as well as the categorical breakdown of the sector.

1. Health Technology Market Overview

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Clinical Administration and Backend: Services that foster management of administrative tasks such as scheduling, patient transfers, billing, compliance, etc.

Digital Medical Devices & Diagnostics: New generation of IT-enabled medical devices and diagnostic tools for use by doctors and other clinical staff.

Population Health Management: Services to manage healthcare issues for groups of people such as corporate employees.

Genomics and Personalized Medicine: Services that utilize human genome data for analytics, disease prevention, and the like.

Electronic Health/Medical Records: Services that create or manage EHR/EMR (Electronic Health/Medical Records) to improve efficiency/effectiveness of medical practice.

Doctor Network and Resources: Social services that allow doctors to connect with each other to get in dialogue and/or access their expertise.

Medical Big Data: Big data and analytics for medical applications.

IoT Health Care: Internet of Things (IoT) focused on consumer and/or at-home health care solutions.

Doctor and Healthcare Service Search: Services that allow patients to search for doctors, healthcare plans, and other healthcare services.

Remote Monitoring and Family Care Management: Services that allow families and medical professionals to monitor and manage those in care (ie. senior citizens).

teleHealth: Services that allow remote treatment and/or consultation between doctors and patients.

Online Health Destination Sites: Websites providing health-related information and resources.

Health Insurance and Payments: Health insurance exchanges, benefits and patient payment management platforms focused on providing more efficient workflow and greater transparency.

Patient Engagement and Education: Services and platforms such as In-Hospital multimedia systems and patient relationship management services.

Mobile Fitness/Health Apps: Mobile apps that keep track of fitness activities, provide health resources, training programs, etc.

IoT Fitness: Internet of Things (IoT) focused on personal fitness and wellness solutions.

Online Health Communities: Social services among patient groups and medical professionals.

Healthcare Marketing and Campaign Management: Services for hospitals, insurance agencies, and other healthcare services to identify and target potential customers.

Healthcare Mobile Communications/Messaging: Mobile communications services dedicated for hospital use by doctors, nurses, etc.

Gamification of Health: Application of game elements to promote behavior-changing health and wellness.

Healthcare Robotics: Robotics application for healthcare such as prosthetics, remote treatment, etc.

Healthcare Startup Incubators and Accelerators: Investor programs that fund and support Digital Health startups.

2. Number of Companies Per Category

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The bar graph above summarizes the number of companies in each Health Technology category to show which are dominating the current market. Currently, the “IoT Health Care” category is leading the way with a total of 123 companies, followed by “IoT Fitness” with 97 companies.

3. Average Funding By Category

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The bar graph above summarizes the average company funding per Health Technology category. The “Health Insurance/Payments” category leads the way with an average of $58.5M per funded company. The Health Insurance/Payments category includes health insurance exchanges, benefits and patient payment management platforms focused on providing more efficient workflow and greater transparency.

4. Venture Investing in Health Technologies

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The graph above compares total venture funding in Health Technology to the number of companies in each category. The “Genomics & Personalized Medicine” and “Health Insurance/Payments” categories seem to be the ones with the most traction.

5. Global Breakdown of Health Technology

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The following infographic is an updated heat map indicating where Health Technology startups exist across 30 countries and 327 cities. Currently, the United States is leading the way with 706 companies. The United Kingdom is in second with 25 companies followed by Canada with 24.

6. Median Age of Health Technology Categories

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The bar graph above summarizes Health Technology by median age of category. The “Electronic Health Records” category has the highest median age at 9 years, followed by “Clinical Admisnitration” and “Online Health Destination Sites” at 8 years.

As Health Technology continues to develop, so too will its moving parts. We hope this post provides some big picture clarity on this booming industry.

Venture Scanner enables corporations to research, identify, and connect with the most innovative technologies and companies. We do this through a unique combination of our data, technology, and expert analysts. If you have any questions, reach out to [email protected].

The State of the Future of Television in Six Visuals

We cover many emerging markets in the startup ecosystem. We previously published posts that summarized Financial Technology, Internet of ThingsBitcoin, MarTech, Artificial Intelligence, Retail Technology, Health Technology, and Connected Transportation in six visuals. This week, we do the same with the Future of TV. At this time, we are tracking 664 Future of TV companies across 11 categories, with a combined funding amount of $13.5B. To see all of our Future of TV related posts, click here!

The six Future of TV visuals below help make sense of this dynamic market:

  1. Market Overview: Breakdown of Future of TV into categories.
  2. Number of Companies Per Category: Bar graph summarizing the number of companies in each Future of TV category.
  3. Average Funding By Category: Bar graph summarizing average company funding per Future of TV category.
  4. Venture Funding in Future of TV: Graph comparing total venture funding in Future of TV to the number of companies in each category.
  5. Global Breakdown of Future of TV: Heat map indicating where Future of TV companies exist.
  6. Median Age of Future of TV Categories: Bar graph of each Future of TV category by median age.

Below you’ll find our Future of TV sector map as well as the categorical breakdown of the sector.

1. Future of TV Market Overview

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Video Consumption Platforms: Video Consumption Platforms enable users to consume television content through the Internet and across multiple screens. They include destination and over-the-top video platforms, as well as set-top boxes and connected TV devices.

Social Video Platforms: Social networks built around video/TV content, and applications used by the end-users alongside TV programs to offer enhanced viewing experiences.

Video Advertising Platforms: Video Advertising Platforms include ad networks that help marketers by finding and aggregating the supply of publisher inventory, ad servers that facilitate the delivery of ads from a stored server, and marketplaces that connect buyers and sellers over digital advertising space.

Content Distribution Platforms: Companies that provide a network of servers to deliver content to users based on their geographical location, and platforms that enable users to upload their videos and automatically distribute content across a variety of destinations.

Content Management Platforms: Content Management Platforms handle the organization of video content such as processing videos for uploading, managing ad operations, and tagging video content with metadata to enhance targeted advertising.

Video Creation Platforms: Video creation platforms enable users to create or produce video content to be distributed across the Internet or other medium.

Video Infrastructure Platforms: Video Infrastructure Platforms provide the backend system that support video streaming services. These include general infrastructure platforms as well as data management platforms that store and utilize user demographics and consumption data.

Multi-channel networks (MCN): Multi-channel networks are entities that aggregate content from multiple YouTube publishers into one channel.

Video Licensing Platforms: Video Licensing Platforms manage and monetize the copyright of television, film, and digital video content and syndicate them with advertisements to deliver to publishers.

Video Analytics Platforms: Video Analytics Platforms measure and provide viewer analytics and social media data around TV shows to publishers and content creators.

Video Discovery Platforms: Companies that help users find and curate relevant video content based on preferences and data analysis, as well as providing viewers with supplemental TV program information (e.g. descriptions, showtimes).

2. Number of Companies Per Category

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The bar graph above summarizes the number of companies in each Future of TV category to show which are dominating the current market. Currently, the “Video Advertising” category is leading the way with a total of 132. The category with the least number of companies is “Video Licensing” with 32 companies.

3. Average Funding By Category

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The bar graph above summarizes the average company funding per Future of TV category. The “Video Creation” category leads the way with an average of $67.6M per funded company. The Video Creation category includes platforms that enable users to create or produce video content to be distributed across the Internet or other medium.

4. Venture Investing in Future of TV

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The graph above compares total venture funding in Future of TV to the number of companies in each category. The “Video Consumption” and “Social Video” categories seem to be the ones with the most traction.

5. Global Breakdown of Future of TV

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The following infographic is an updated heat map indicating where Future of TV startups exist across 33 countries and 202 cities. Currently, the United States is leading the way with 383 companies. The United Kingdom is in second with 45 companies followed by Israel with 18.

6. Median Age of Future of TV Categories

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The bar graph above summarizes Future of TV by median age of category. The “Content Management” category has the highest median age at 9 years, followed by “Video Infrastructure” at 8.5 years.

7. Recent Trends in the Future of TV

Some of the more recent trends we’re seeing in the sector include the following:

The rise of second screen and viewer participation — As viewers consume video content on television, most of them are also engaging on social media and other websites through another device. Nielson data estimates that 85% of American television viewers are also browsing on a second screen while watching television. Viewer participation has also moved from the background to the foreground, as viewers no longer just sit back passively and comment through social media, but actively influence the production of the content by voicing their opinions about it. (Source)

The growing popularity of mobile content — With the prevalence of mobile devices, the quality of mobile video content has also grown drastically. With better compensation and less executive intervention, talented writers are increasingly moving from the film industry to the television industry, making premium television content now available to anyone through all devices. Another trend is that viewers are now watching longer and longer video content through mobile devices, contrary to the previous prediction that only minute-long video content would be consumed on mobile. (Source)

As the Future of TV continues to develop, so too will its moving parts. We hope this post provides some big picture clarity on this booming industry.

Venture Scanner enables corporations to research, identify, and connect with the most innovative technologies and companies. We do this through a unique combination of our data, technology, and expert analysts. If you have any questions, reach out to [email protected].

Making Sense of the IoT Ecosystem

At this time, we are tracking 1010 Internet of Things (IoT) companies across 16 categories, with a combined funding amount of $14.3B. These are companies and categories that involve anything and everything that is IoT. To see the full list of 1010 Internet of Things companies, contact us using the form on www.venturescanner.com.

IoT Map Gif

Home: Internet of Things focused on residential segment. Solutions include home security, automation, energy management, etc.

User Interface: Hardware that offers new ways to view and/or control digital devices and applications.

Lifestyle and Entertainment: Hobby and lifestyle segments such as music, gardening, cooking, pet care, etc.

City and Infrastructure: Smart City and Infrastructure verticals.

Platforms and Components: Platforms that enable machine to machine (M2M) communication.

Fitness: Personal fitness and wellness solutions.

Health Care: Consumer and/or at-home health care solutions.

Automotive: M2M in the automotive industry.

Toys: Products aimed at the kids market.

Agriculture: Companies that enhance productivity of the agricultural and farming industries.

Enterprise: IoT focusing on enterprise applications.

Smart Watches: Devices in wristwatch form that include built-in sensors and connectivity.

Tags and Trackers: Small wireless tags used to locate and find things by attaching them to smartphones and personal items.

Jewelry: IoT that puts fashion first. These devices offer features such as notifications for calls and messages, personal security, etc.

Retail: Physical devices that have retail applications (e.g. beacons).

Venture Scanner enables corporations to research, identify, and connect with the most innovative technologies and companies. We do this through a unique combination of our data, technology, and expert analysts. If you have any questions, reach out to [email protected].

Insurance Technology Funding by Category

The following infographic summarizes the total funding of all the companies within each Insurance Technology category. You could see that Health Insurance has the highest funding amount at $1.91 Billion, followed by Auto Insurance at $1.12 Billion. At Venture Scanner, we are currently tracking over 535 Insurance Technology companies in 13 categories across 47 countries, with a total of $4.63 Billion in funding. To see the full list of 535 Insurance Technology companies, contact us using the form on www.venturescanner.com.

InsurTech Funding by Category Gif

Venture Scanner enables corporations to research, identify, and connect with the most innovative technologies and companies. We do this through a unique combination of our data, technology, and expert analysts. If you have any questions, reach out to [email protected].