Artificial Intelligence Companies Founded by Year – Q3 2017

The following graph shows the founding year distribution in the Artificial Intelligence sector. The graphic includes data through July 2017.

Artificial Intelligence Companies Founded by Year
Artificial Intelligence Companies Founded by Year

The above graph summarizes the number of Artificial Intelligence companies founded in a certain year. 2014 ranks at the top with around 259 companies founded in that year alone. 2013 is the runner-up with 244 companies founded in that year.

We are currently tracking 1942 Artificial Intelligence companies in 13 categories across 70 countries, with a total of $23 Billion in funding. Click here to learn more about the full Artificial Intelligence market report.

Artificial Intelligence Funding Trends – Q3 2017

The following graphs highlight recent trends in Artificial Intelligence (AI) startup funding activity. The graphics include data through July 2017.

AI Q3 2017 Funding by Year

The above graph summarizes the total funding raised by AI startups for each year. 2017 has the most funding to date at just over $6B.

AI Q3 2017 Funding by Vintage Year

The above graph summarizes the total amount of funding raised by AI companies founded in a certain year. Companies founded in 2012 have raised the most funding around $4B.

We are currently tracking 1,931 AI companies in 13 categories across 70 countries, with a total of $22 Billion in funding. Click here to learn more about the full Artificial Intelligence market report.

Artificial Intelligence Funding by Round – Q3 2017

The following two graphs summarize the rounds of funding going into the Artificial Intelligence (AI) space. Please note these graphics are made using data through July 2017.

Artificial Intelligence Funding Amount by Round
Artificial Intelligence Funding Amount by Round

The graph above shows the total amount of VC funding broken out by round. From 2006 to 2016, we saw a general increase in the overall sector funding, with the total amount peaking in 2016. Earlier stage funding rounds (Series A, B, and C) made up most of the funding amount.

Artificial Intelligence Funding Count by Round
Artificial Intelligence Funding Count by Round

The graph above shows the total count of funding events broken out by round. From 2006 to 2016 we’ve seen a general upward trend that peaked in 2014 and 2015, and then declined slightly in 2016. Earlier stage funding such as Seed, Series A, and Series B events make up the majority of funding event counts.

We are currently tracking 1917 Artificial Intelligence companies in 13 categories across 70 countries, with a total of $21.5 Billion in funding. Click here to learn more about the full Artificial Intelligence market report.

Artificial Intelligence Activity by Selected Investors – Q3 2017

The following graph summarizes investor activity in the Artificial Intelligence (AI) space. Please note these graphics are made using data through July 2017.

AI Investor Activity Q3 2017

The above analysis summarizes the total number of investment rounds AI investors participated in, and the number of unique companies funded by those investors. Major investors into the space include Y Combinator, NEA, Sequoia Capital, 500 Startups, and CE Ventures.

We are currently tracking 1,906 AI companies in 13 categories across 70 countries, with a total of $19 Billion in funding. Click here to learn more about the full Artificial Intelligence market report.

Artificial Intelligence Exits by Category and by Year – Q3 2017

The following graphs highlight the exit activity in the Artificial Intelligence sector. The graphics include data through July 2017.

Artificial Intelligence Exits by Category
Artificial Intelligence Exits by Category

The above graph summarizes the number of exits (acquisitions and IPOs) in each Artificial Intelligence category. The Machine Learning Applications category leads the sector with 4 IPOs and 43 acquisitions. The Natural Language Processing category is the runner-up with 4 IPOs and 29 acquisitions.

Artificial Intelligence Exits by Year
Artificial Intelligence Exits by Year

The above graph summarizes the number of exits (acquisitions and IPOs) in Artificial Intelligence by year. 2017 currently leads the sector with 1 IPO and 41 acquisitions, with 2016 following behind with 39 acquisitions.

We are currently tracking 1896 Artificial Intelligence companies in 13 categories across 70 countries, with a total of $19B in funding. Click here to learn more about the full Artificial Intelligence market report.

Artificial Intelligence Market Overview and Innovation Quadrant – Q3 2017

The following post highlights how Venture Scanner categorizes the Artificial Intelligence (AI) startup landscape, and presents our Innovation Quadrant showing how those categories compare to one another. The data for this post is through July 2017.

AI Logo Map Q3 2017

The above sector map organizes the sector into 13 categories and shows a sampling of companies in each category.

AI Innovaiton Quadrant Q3 2017

Our Innovation Quadrant provides a snapshot of the average funding and average age for the different AI categories and how they compare with one another.

  • Heavyweights: These categories are comprised of companies that have reached maturity with significant financing.
  • Established: These categories are comprised of companies that have reached maturity with less financing.
  • Disruptors: These categories are comprised of companies that are less mature with significant financing.
  • Pioneers: These categories are comprised of companies that are less mature with earlier stages of financing.

The definitions of the AI categories are as follows

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.

Computer Vision/Image Recognition Platforms: 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.

Context Aware Computing: Companies that product 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.

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.

Deep Learning/Machine Learning Platforms: 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.

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.

Natural Language Processing: 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.

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

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.

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.

Speech to Speech Translation: Companies that recognize and translate 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.

Virtual 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.

We are currently tracking 1,888 AI companies in 13 categories across 70 countries, with a total of $19 Billion in funding. Click here to learn more about the full Artificial Intelligence market report.

Venture Investing in Artificial Intelligence through Q3 2017

The following graphs highlight venture investing trends into the Artificial Intelligence (AI) sector. The graphics include data through July 2017.

AI Venture Investing Q3 2017

The above graph compares the total venture funding in each AI category to the number of companies in the category. The Machine Learning Applications category leads in both stats, with over $8B in funding and around 575 startups.

AI Q3 2017 Average Funding by Category

The above analysis summarizes the average company funding in each AI category. The Smart Robots category leads the sector with just over $35M in average funding per company, followed by the Recommendation Engine and Machine Learning Platform categories.

We are currently tracking 1,884 AI companies in 13 categories across 70 countries, with a total of $18.5 Billion in funding. Click here to learn more about the full Artificial Intelligence market report.