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Artificial Intelligence Startups

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Last Updated: 02 July 2021

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General | Latest Info

Artificial Intelligence-AI-is currently among the most disruptive Technologies, and a great means for startups to achieve their hyper-Growth targets. With a number of applications in big data, computer Vision, natural language processing, and more, AI is revolutionizing businesses, industries, and people's lives. Ai Technology Startups are attracting the attention of multiple investors across the globe, and particularly so in the US and China. In very best-fund and most promising independent startups, most AI companies hail either from the US or China, with a few more countries represent. In both of these key countries, benefits of AI are clear in a number of industries, but the focus of each country seems to be slightly different. The largest American AI startups are particularly present in the fields of big data Analytics and process automation for Business, autonomous driving, and biotechnology. However, largest Chinese AI startups tend to be more developed in computer Vision, AI for Internet of Things and hardware, and facial recognition for applications in public Security, Financial Security, and payments. For good measure, it is important to remark that three British startups are also present on top, denoting early interest and effectiveness of UK companies in AI, together with Canadian and Singaporean company. Nevertheless, we should note that the following ranking only includes companies that are primarily operating with AI at their core and not just adding a few algorithms that use some AI to accompany their non-AI businesses. Nowadays, many companies use artificial Intelligence Algorithms in some of their secondary processes, boasting being AI companies just as a marketing tactic. That why companies listed here are only startups that are built upon AI. They all process big data with machine Learning Algorithms at the center of their value proposition, in fields that are traditionally associated with AI: recognizing patterns in videos, images, and visual data, optimizing AI Algorithms performance, processing large amounts of textual data to extract Insights or generating new text, analyzing genetic data, or creating robots. Some of these startups are already famous in their field, having reached recognition for their products and services. But many are not very well know, as they focus on certain business markets and take charge of problems faced in specific verticals. Many of the 30 startups present hereafter have already reached Unicorn status, that is to say, valuation of more than a billion dollars. For a complete list of world Unicorn Startups, and much more information on each company, including its valuation, funds raise, know investors, website link, and description, check our 580 Unicorn Startup Companies Excel Spreadsheet.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Funding for AI in Healthcare

This category includes companies that focus on Clinical trial Management. Building upon more robust datasets, startups in this category help researchers recruit and retain patients, as well as design and manage their studies. One startup applying AI to clinical trial processes is Teckro, Ireland-base company that provides researchers with a machine learning-driven platform for monitoring trial progress across geographically dispersed teams. The company has raised 41M in disclosed equity funding, with participating investors including Founders Fund and Sands Capital, among others. Deep Lens, another startup in this category, uses an AI-base Pathology platform called VIPER to identify eligible trial candidates at the point of their diagnosis. The company has attracted 17. 2m in disclosed equity funding, with notable investors including Rev1 Ventures, Sierra Ventures, and Ohio TechAngels. Startups in this category are developing AI-Drive privacy solutions for Healthcare administrators, such as secure transfer of patient data. For example, Baltimore-base Protenus provides Healthcare systems with AI-powered auditing, compliance Analytics, and security software for patient and Clinical Trials Data. It has raised 36. 15m in disclosed equity funding. Similarly, Datavant is a San Francisco-base startup that deidentifies patient data so that it can be safely Package and exchanged with Healthcare Partners. Datavant has raised 40. 5m in disclosed equity funding from Roivant Sciences and CEO Travis May. These companies leverage AI to find the most effective combinations of drug compounds, reducing time and capital required for Drug Discovery. Two different business models have emerged in this segment: biotechnology startups that are conducting internal R & D to discover new drugs, and pureplay SaaS startups that sell Analytics software to pharmaceutical companies. Among the most well-Fund startups in this category are Recursion Pharmaceuticals and Blackthorn Therapeutics, AI biotech companies with drug development pipelines. Recursion Pharmaceuticals, Salt Lake City-base company backed by CRV and Lux Capital, manages a pipeline of drugs for cardiology, neurology, dermatology, hematology, immunology, ophthalmology, and other focus areas. The company has raised 235. 77m in disclosed equity funding. San Francisco-base Blackthorn Therapeutics is backed by Google Ventures and Polaris Partners. It has developed a pipeline of neurobehavioral Therapeutics to treat mood and anxiety disorders, autism, and other neurological disorders. The company has raised 130M in disclosed equity funding. Startups in this category include AI-driven wellness applications that let consumers track their health and fitness metrics. Tokyo-base FiNC, for example, uses an AI-driven chatbot to provide personalized recommendations to help users achieve their exercise, sleep, and nutrition goals. Startup has secure 66. 28m in disclosed equity funding. Startups in this category are using AI for personalized Healthcare, genome sequencing, and CRISPR Research. One startup working in space is WuXi NextCODE, Massachusetts-base startup that applies AI and deep learning to genomic analysis. This research is used to improve patient sampling for Drug Discovery and accelerate cancer research. The company has raised 455M in disclosed equity funding, including 200M Series C led by Ireland Strategic Investment Fund in November 2018. Another startup developing AI-driven genomic solutions is South Korea-base Syntekabio, which analyzes individuals ' unique genetic maps to provide Personalized Medical treatments.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Keeping Cyber Networks Healthy

Cybersecurity Companies Leveraging Machine Learning And Artificial Intelligence (AI)

CompanyDescriptionTotal Disclosed Funding $MSelect Investors
TaniumA real-time endpoint management solution that provides instant visibility into networked devices through natural language processing, to allow enterprises to collect data and update machines across networks.$295MExecutive Press, Andreessen Horowitz, Nor-Cal Invest
CylanceApplies AI algorithms to predict, identify and stop malware and mitigate damages from zero-day attacks.$177MKhosla Ventures, Fairhaven Capital, Citi Ventures
LogRhythmOffers threat intelligence and analytics, for organizations to rapidly detect, respond to and neutralize threats, in addition to compliance automation and assurance, and enhanced IT intelligence.$126MAccess Venture Partners, Siemens Venture Capital, Exclusive Ventures
DarktracePairs behavioral analytics with advanced mathematics to automatically detect abnormal behavior in organizations.$107MSoftBank Group, Samsung Ventures, Ten Eleven Ventures
Sift ScienceProvides real-time machine learning fraud prevention solutions for online businesses.$54MUnion Square Ventures, Spark Capital, SV Angel
ExabeamOffers user behavior analytics that leverage existing log data to quickly detect advanced attacks, prioritize incidents and guide effective responses.$35MAspect Ventures, Icon Ventures, Norwest Venture Partners
E8 SecurityProvides intelligence and analytics software alongside a big data platform for long-term data retention and retrospective analysis.$22MAllegis Capital, March Capital Partners, Strategic Cyber Ventures
CyberXDesigned for industrial internet networks to detect abnormal behavior by analyzing the operational behavior of the networks.$11Mff Venture Capital, Flint Capital, GlenRock Israel
IntersetOffers behavioral analytics to protect critical data across the manufacturing, life sciences, high-tech, finance, government, aerospace and defense, and securities brokerage industries.$10MIn-Q-Tel, Anthem Venture Partners, Telesystem
PatternExA platform to identify malicious user intent by enabling users to predict and prevent cyber attacks in real time, across an enterprise network.$8MKhosla Ventures
SecBIOffers an advanced threat detection system that uncovers cyber attacks, including all affected users, domains, assets and more.$5MAmichai Shulman, Connecticut Innovations, Jerusalem Venture Partners
Avata IntelligenceDelivers descriptive, diagnostic, predictive, and prescriptive analytics to understand and respond to security threats.$2.5MAristos Ventures
Jask LabsLeverages artificial intelligence and advanced analytics to keep corporate data and operations secure.$2MBattery Ventures, Vertical Venture Partners, Undisclosed Investors

There are 8 705 startups and companies listed in Crunchbase today who are relying on Machine Learning for their main and ancillary applications, products, and services. 83% of Machine Learning startups Crunchbase tracks have had just three Funding rounds or less, with Seed, Angel and early-stage round being the most common. Artificial Intelligence-related companies raised 9. 3b in 2018, a 72% increase over 2017, according to PwC / CB Insights MoneyTree Report, Q4 2018. Artificial Intelligence deals increased in Q1 2019 to 116 deals, up from 104 deals in Q4 2018 according to the latest PwC / CB Insights MoneyTree Report Q1 2019. Ai-base Marketing patents are a fasting growing global category, reaching a Compound Annual Growth Rate Of 29. 3% between 2010 and 2018, according to EconSight. From powering personalized career sites that recommend open positions that are ideal for giving candidates based on their capabilities as Eightfold. Ai do today, to scale the complexity and volume of Machine Learning algorithms, so they are more accessible as DataRobot do, Machine Learning startups are taking on many of business's most significant challenges. Ai and Machine Learning have the potential to create additional 2. 6t in value by 2020 in Marketing and Sales, and up to 2T in Manufacturing and Supply Chain planning, according to McKinsey Global Institute. Please see the latest roundup of Machine Learning Forecasts and Market Estimates, 2019 for more Market Data on Machine Learning exponential Growth. Alation-alation offers Machine Learning Data Catalog to help people find, understand, and trust data across their organizations. Theyve defined their solution to align with the needs of four dominant personas, including Chief Data Officers, Analysts, Stewards, and IT and Engineering. Their Data Catalog is known for its usability and intuitive design. More than 100 organizations, including City Of San Diego, eBay, Munich Re, and Pfizer, have adopted Alation Data Catalog. Alation is Fund by Costanoa Ventures, DCVC, Harmony Partners, Icon Ventures, Salesforce Ventures, and Sapphire Ventures. Alation has raised a total of 82M in funding over four rounds. Their latest funding was raised on Jan 17 2019, from the Series C round. Anodot-capitalizes on the innate strengths of Machine Learning by continually looking for patterns using constraint-base modeling across diverse data sets, businesses rely on to operate daily. Similar to many Machine Learning startups that capitalize on technology's ability to learn continually, Anodots AI Platform looks to eliminate blind spots in data and quantify root-causes in diverse data sets. Anodots Autonomous Analytics Platform leverages advanced Machine Learning techniques to constantly analyze and correlate every business parameter, providing real-time alerts and forecasts, in their context, lowering time to detection and resolution. Anodot raised total of 27. 5m in Funding over four rounds. The latest Funding came from the 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.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Deepfakes Get a Friendly Makeover

Xuan Yong and Mike Witte don't have the same name recognition in the tech industry as Mark Zuckerberg, Evan Spiegel or Whitney Wolfe Herd. But like those three more recognizable founders, Yong and Witte also have unicorn Founder list on their resumes. Pair is behind RigUp, Austin-base startup that provides digital workforce and vendor management tools to companies in the oil and energy industry. Launch in 2015, company land valuation of more than 1 billion last year after raising 360 million in funding. Rigup brought a business model validated by countless tech companies digital marketplace connecting users with workers on-demand to an industry that isn't exactly known for having an active startup scene. Solving problems in industries traditionally overlooked by entrepreneurs is a strategy many Austin founders have employed with great success. Consider the real estate industry, which is increasingly attracting the attention of local founders thanks in part to the accomplishments of companies like Opcity. Real estate tech company, which matches agents with pre-screen home buyers, raised 27 million in funding before IT was acquired by realtor. Com in summer of 2018 for 210 million. And, although Austin might not seem like a hotbed for insurance technology, insurance comparison site Zebra raise 38. 5 million in February and local meetup group for industry professionals, InsureTech ATX, boasts over 500 members. Rigup, Opcity and Zebra are far from the only tech companies in Austin that have found success by bringing tech to industries that have been slower to embrace digitalization. Here are three more Austin tech companies hoping to make a mark in the oil and energy, real estate and insurance industries. Anand Jayaramanna, engineer working with a startup in Bengaluru, was literally shown door last week as the company could not withstand a sudden slowdown in business due to coronavirus Lockdown. It was all very sudden, and they did not give the US any notice. I only have savings for the next three months. After that, it is going to be hard for me, says Jayaramanna. This shows the unprecedented challenge that startups may have to face in coming months if the spread of the novel coronavirus is not contain. The threat of job losses has now raised its ugly head on the startup ecosystem, which provides employment, directly or indirectly, to little more than half a million people, according to various reports. According to Nasscom, Indian IT Industry's trade body, Indian startups create an estimated 60 000 direct jobs and 1. 3-1. 8 lakh indirect employment in year 2019. Seattle-base augmented writing startup Textio has closed a 12 million funding round as the company looks to expand beyond the enterprise market. The news comes on heels of cutbacks at a 6-year-old startup, which saw the reduction of 20 percent of its staff last week.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Final Thoughts:

From redefining management by evaluating job candidates on innate and emerging strengths by removing conscious and unconscious biases from hiring decisions as eightfold. Ai do today to providing self-service AI platform that is always learning from analytics as Anodot does Machine Learning startups are fascinating to track. International Data Corporation 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. Please see the latest roundup of Machine Learning forecasts and market estimates, 2018 for more market data on Machine Learning's exponential growth. Ai will be a true differentiator for companies in the future. Companies that have mastered it will take off, those who haven't will dwindle, Scott Stephenson, Founder, and CEO of Deepgram, automatic speech recognition company, told Crunchbase News in an email. 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 is based on analysis of their ability to attract new customers, current and projected revenue growth, patent current value and potential, and position in their chosen markets. Co-founder and CTO of Skyline AI, Artificial Intelligence company in the commercial real estate industry, believes that weve reached the renaissance age in AI. We consider companies in Artificial Intelligence, Machine Learning and adjacent categories. Include in the list are active startups that have raised at least one venture capital round since January 1 2016. The list includes companies that are working specifically on Artificial Intelligence and Machine Learning technologies. Startups are ranked based on know total funds raise.


Determined AI

Ai startups are getting sold like hot cakes because they are building products, which are capable of solving business problems as efficiently as human beings in various aspects. Large scale automation and the Internet of Things and enabling a world of limitless possibilities. These startup - ideas are innovative. These people are thinking ahead of time. With awesome product, they may fail to create a large impact, but the backing of giant tech sharks provides them with access to much needed resources. Recipes for building such products come from machine learning. Yes, using data and machine learning, you can also build program,s which train, learn and deliver results better than humans. But, it is not easy. Had it been easy, every other block in your neighborhood would be prospering with AI startup. Let's look at some of the problems being solved by AI startups: recognizing characters from images Improving voice recognition in native languages Detecting malicious patterns in web applications Creating driverless vehicles Predicting stock performances with better accuracy Speech translation Developing intelligent chat bots Build games which challenge human intuition Improving efficiency of product deliveries Detecting fraudulent behavior in humans Detecting human diseases or epidemic Improving user experience on Internet and, there are many others. Do you study common pattern?Ss All of these problems are ones which have prevailed over decades, but haven't found a solid solution. That is why artificial intelligence has taken initiative. Do humans really need to worry?

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Smart stuff everywhere

Directly taking on Google and Amazon generally seems to be an ill-advise strategy for young startup. It is even more complicated when youre competing on home assistants front, technically complex, capital-intensive future platform into which both tech giants have dumped substantial sums. Over the past few years, small Smart home startup Josh. Ai has attempted to do just that, capitalizing on public distrust of big voice platforms to sell intelligent Assistant to users weary of sticking Google or Amazon-own microphone in their homes. The company has built its business catering to customers seeking professionally instal pricey outfits in their home, costing upwards of 10 000 on high end. The company just secured its largest funding round to date, 11 million Series round, which brings the startup's total funding to 22 million. Spokesperson for Josh. Ai said their investors have asked not to be name, though he confirmed the round was led by corporate investors. For people with Echo Dot or Google Mini in their home, Josh. Ais approach feels familiar. The platform boasts a number of third-party integrations, so you can use the platform to switch off lights, turn on devices, play music and answer some simple commands. Basically, bulk of home-centric commands are popular on Google Assistant and Alexa. Startup recently introduced Josh Micro, its own take on Echo Dot. It has a futuristic vibe and, because it is instal by professionals, users are privy to sleek look with wires neatly tucked away inside walls. Ceo Alex Capecelatro say their competitors in professionally installed space have been pushing wall-mount screens with UIs that often arent updated and do age well. He hops their more low-key display-free devices can keep less focus on hardware and more attention on their software. Our philosophy is that you should be talking to a puck, it should feel fully immersive, he say. Capecelatro had originally seen the best path to existing alongside Google and Amazon as working with them and leveraging their platforms, but he soon found that not working with them proved to be startups biggest asset. In terms of direction, what has become really clear in the past three years was the importance of privacy, Capecelatro told TechCrunch. A lot of our clients are just people who care about their privacy; it is part of every conversation. On the tech side, Capecelatro says startups platform is designed around its own natural language processing stack, so most voice requests can be processed locally, though startup do leverage technology built by Google and Microsoft to handle speech-to-text processes. While companies use anonymized data to improve their services, startups have also introduced specific software features to keep privacy-focused users satisfied, including their own take on Smart home incognito mode. There are few silver bullets in Smart home tech, and robust third-party support often leaves room for uncertainty, which in Josh's case could mean the difference between lights turning on or staying off.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Sources

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

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