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70 Best Startups You Need to Watch Out for in 2019

With every new day, we are inching towards an AI-first world, and this is a great time for tech startups to make their mark.

As we all know AI and robots are the way to the future, a number of the Venture Capital firms and tech investors are having a bird’s eye view of the tech industry for all the novel ideas that you can turn into reality.

But since there are hundreds of new startups launching every day, the real question is: How can you filter out the best startups that will flourish in 2019?

Here is a list of the most promising new startups of 2019 based on their success stories, uniqueness and the venture-backed funding they have raised so far.

Don’t take our word, Read Cloudways Hosting Reviews Please note: This is not a comprehensive list of startup companies and neither is any startup placed in any ranking order.

The tech startup is famous for creating a shared-inbox platform that allows teams to handle incoming messages in a seamless way.

This new startup combines messages from four channels including email, texts, Slack, and social media, at a single place.

It has already started trials in the UK, and aims to bring supervised trial cars to the major freeways by 2019.

This new startup helps you do business, make friends, and even fall in love with anyone across the globe without language becoming a barrier.

Dandelion is a startup, focusing on geothermal pump installations to harness energy from below the Earth’s surface to keep homes hot and cold during different seasons.

The geothermal installation will keep the homes cool in Summer by pumping heat away from home into the Earth’s crust, and in Winter keeps it warm by pumping back heat from below the Earth into the house.

Deep Map offers high-definition maps for self-driving cars, hence, helping them easily navigate around the city without any obstruction.

You can easily integrate the maps with any fleet of self-driving cars, and grow as more data becomes available.

Footloose is an automated litter box that can self-clean itself, monitors the health of critter including the amount of litter and the time it takes for a cat to do it.

The company asked for $50,000 in funding to start mass production but instead received more than $1.5 million.

It uses AI-based prediction models and a few data scientists who translate the numbers into visual representations that the store owners can understand.

It helps you imagine the home decoration experience before you actually buy the product using your smartphone camera and the app.

The app uses computer vision and image recognition technology to help users envision the way their home will look like with furniture.

They took a one-ticket flight to the USA and started working on this amazing product that can bring the stories of books alive through AR.

It develops photo-realistic full-color 3D-models and mini-replicas of almost everything ranging from 3D full body printing, to color modeling, to human model printing.

But Bundil lets consumers automatically invest their spare change from credit or debit card purchases into various forms of cryptocurrency, including Bitcoin, Ethereum, LiteCoin and Bitcoin Cash.

The platform combines everyday transactions including buying coffee or lunch, drilling down to zero and invests the resulting spare change into cryptocurrency.

Being led by a former banking professional, this startup aims to replace regular currency transactions with cryptocurrencies.

Civil is bringing a change in the way journalism currently works and helps journalists by providing resources and funding to the users.

Only time will tell how successful it will become, but with funding of a whopping $15million, we can assume it will be pretty soon.

The results of profits of this top startup won’t be available in 2019, because cancer research is an ongoing process and will probably bear the fruits in the next few years.

The CEO also found a spot in Forbes’ under 30 CEOs under 30 list in the medical devices startup section, for a breakthrough technology working to monitor and curb diabetics.

Sano has partnered with Fitbit to make it easier for people to monitor glucose level in their blood directly by using the watch.

The toothbrushes are available for $40 and cost $5 for brush-top replacement after three months.

Kinetic Reflex is a smart wearable device that reduces the incidences of workplace injuries by monitoring data and providing insights on a regular basis With Kinetic Reflex, you can easily set your own goals and practice beating them.

The device detects high-risk postures, provides workers with feedback whenever high-risk motions occur, and uses biomechanics, to reduce the risk of injuries and improving well-being.

Whenever you’re stressed or anxious or having trouble sleeping, Aura Health will provide you with complete peace of mind by providing motivating stories, meditation, and coaching.

Jaga-Me team is a not-for-profit company working for terminally ill patients by providing them palliative care at home.

The team behind the bag went for crowdfunding with a request for $500k but instead received $5.2 million.

Park and Diamond company develop protection gear, for cycles that are compact, small, and easy to put inside a pant pocket.

Not only it has this service but it is widely in use in various e-commerce stores to keep themselves compliant of the laws of the state and for fraud detection and prevention.

He thought wouldn’t it be great to develop a product that he can use when going surfing, cycling or somewhere else without the need to carry a wallet or smartphone.

The service will only cost users $24 and they will get a half-inch SIM card that acts as a contactless credit card.

It offers a platform where you can put the required information about a particular document, and then semi-automate the creation process. Checkbox is one of the top startups that truly holds the power to revolutionize the concept and practice of how we do work, and can even put many document creating companies out of business.

TransferGo is a global money transfer company that allows its users to send money from one country to another without paying excessive transaction fees to banks.

The service has licensed under the Financial Conduct Authority (FCA) and can transfer money overseas with the help of a digital account-to-account business model.

The users won’t even need to learn to programme to do that because the system does the work for them by using drag-drop features.

The students just have to take the classes online and take their papers at the end of each semester to pass the class.

The Abre platform empowers schools to start virtual schooling by providing them the platform and training they require to do so.

Employers complain that the reason they always recruit for entry-level jobs is that employees aren’t prepared to take on senior-level positions in their companies.

It is a platform where professionals who want to learn a new language can connect with translators and professional speakers.

A major benefit of using this system is that students can develop their own learning plan that matches their pace.

It offers tuition sessions of 30 minutes in which students and tutors can interact in one-to-one conversation.

It offers an enjoyable experience, through workshops that help empower local artists from Australia and make art accessible, affordable, and appealing.

This new startup has gained funding from multiple VC firms and investors, and currently has a market value of $55million.

The team has developed its first product named Burro, a self-driving robot that follows the user around and maps the journey, forming a virtual conveyor belt.

Emotix is an AI-Robotics startup working to develop emotionally intelligent robots capable of engaging, educating and entertaining the children above the age of five.

The half-a-foot robot has access to a wide pool of knowledge that it conveys to the child in a conversational tone.

The team behind Emotix understands the fact that most children today, tend to sit in front of a TV set, which isn’t healthy for them.

It is also great for those who want to work on their startups but don’t want to let go off a job that brings them bread and butter.

Zenjob provides a united platform where companies can post temporary staffing requirements, and students can develop their profiles and bid on them.

SaaS startup that focuses on developing software solutions to live stream video content during events.

Unfortunately, mechanics all over the world, don’t have an automated system that tells about the accurate time of car repair.

With $250K funds already in the bank, the founders are working to develop a solution that mechanics can use seamlessly to inform their customers.

In a way, this software solution will completely remove the hassle of fussy conversations between customers and mechanics.

A major reason is the lack of attention and that’s why most developers are unable to build scalable businesses.

It comes in multiple ranges and offers smooth, classic, and long-lasting fire that doesn’t require gas.

The brand does all the heavy lifting including pick and drops from those who are selling their clothes and managing logistics and fulfillment.

The reason behind TrackerHero is that it is highly difficult to track mobile workers who either work remotely or from some other place.

HappyEMI is a Point of Sale (POS) financing service that allows consumers to buy products of their choice on loan and then repay it within time –

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If there’s one topic that makes a radiologist’s eyes widen, it’s any mention of deep learning (DL) and how it will impact their careers.

Whether it’s a fear of being replaced by robots or a genuine interest in the technology, AI and deep learning are hot topics for medical professionals.

While AI was first created in 1956 by computer engineers at Dartmouth College, it was meant to address problems that were difficult for humans to solve but simple for computers.

Scientists knew it was possible for machines to understand and make sense of large volumes of data, they just weren’t sure how to make it happen.

Teaching machines algorithms to parse data, learn from, and make a determination saved scientists time and effort because they no longer had to specify each data point to the computer.

Scientists began testing convolutional neural networks (CNNs), a class of deep, artificial networks that are similar to biological nervous systems.

Unlike machine learning, these networks do not form a cycle, enabling them to make new determinations based on massive quantities of data.

(Source) The fascination spiked in 2012 at the ImageNet Large Scale Visual Recognition Challenge when scientists were able to prove that out of the top 5 labels chosen by deep learning algorithms, the chance that an incorrect label will be included was reduced by 10%.

Getting the most accurate image possible required the medical professionals to intervene in each step of the process, even with advancements in computer film colorization in the 1990s.

When deep learning models are trained with images labeled by experienced radiologists, it has the potential to be a training tool for future or early career professionals.

These particular medical fields lend themselves to deep learning because they typically only require a single image, as opposed to thousands commonly used in advanced diagnostic imaging.

AI 50: America’s Most Promising Artificial Intelligence Companies

Artificial intelligence is infiltrating every industry, allowing vehicles to navigate without drivers, assisting doctors with medical diagnoses, and mimicking the way humans speak.

As Jeremy Achin, CEO of newly minted unicorn DataRobot, puts it: “Everyone knows you have to have machine learning in your story or you’re not sexy.” The inherently broad term gets bandied about so often that it can start to feel meaningless and gets trotted out by companies to gussy up even simple data analysis.

To help cut through the noise, Forbes and data partner Meritech Capital put together a list of private, U.S.-based companies that are wielding some subset of artificial intelligence in a meaningful way and demonstrating real business potential from doing so.

To be included on the list, companies needed to show that techniques like machine learning (where systems learn from data to improve on tasks), natural language processing (which enables programs to “understand” written or spoken language), or computer vision (which relates to how machines “see”) are a core part of their business model and future success.

Only eight startups were founded or cofounded by women, reflecting trends in venture funding, where software startups run by men have received the lion’s share of investment dollars.

Its software cross-references CT images of a patient’s brain with its database of scans and can alert specialists in minutes to early signs of large vessel occlusion strokes that they may have otherwise missed or taken too long to spot.

CEO Wout Brusselaers says the company’s software can pull data from electronic medical records to create patient graphs that allow researchers to filter for specific conditions and traits, leading to matches in “minutes, instead of months.” The system’s language understanding engine has been trained so that it can infer some conditions even if they’re not explicitly mentioned in notes, and Deep 6 says it has more than 20 health system or pharmaceutical customers.

CEO and cofounder Dhananjay Sampath launched Armorblox into the saturated cybersecurity market two years ago with the aim of protecting customers from socially engineered attacks, like phishing emails, that take advantage of human missteps.

“However, the real-world use cases tend to move in the opposite direction—demanding solutions with less compute, memory and power.” They set about trying to create a system where complex algorithms could run on simple hardware and spun out of the Allen Institute, which was cofounded by the late Paul Allen of Microsoft, in 2016.

The company admits that its AI agent, Chloe, is still in its infant stage right now—it can complete simple tasks like reading the instructions on a pill bottle — but it has big ambitions for more robust computer-vision-based navigation.

While chat bots burst onto the scene with a lot of promise (remember how they were going to take over Facebook Messenger?), they never quite reached mainstream adoption, due in part to disenchantment with their limited scope and conversational rigidity.

it just happens to be stuck in a research paper somewhere.” He and longtime Microsoft employee Diego Oppenheimer banded together to devise an easier way for data scientists to discover and work with machine learning models.

The app can build a 3D map of a space in roughly 30 seconds and uses computer vision to recognize real-world objects, so that objects created in AR can interact with them like they would in the real world.

The company recently raised a fresh round of funding led by automotive company Aptiv with the hope that its technology could one day be integrated into smart cars (imagine a vehicle that could issue a warning to a drowsy-looking driver).In the meantime, it’s also being used to test consumer feedback on ads and TV programming.

Blue Hexagon, led by longtime Qualcomm executive Nayeem Islam, spent more than a year and a half building a deep learning system to analyze network traffic that it says can detect and block threats in under a second.

It evaluates data from hundreds of online and offline data sources including credit bureaus, carrier phone records, IP addresses, social networks and more, to monitor for any suspicious behavior.

Chief technology officer Sarjoun Skaff says it has taken iteration after iteration since 2013 to figure out how to let its robots maneuver safely around shoppers and interpret billions of images in a way that was accurate, timely and reliable.

Pymetrics gleans key emotional and cognitive traits for different roles so when job seekers apply to work at one of those companies and complete the challenges themselves, they’re paired with jobs that are the best fit.

The company’s consumer app draws on a data set of more than 2 billion anonymized medical records, finding subtle patterns in the data to give users personalized health advice.

In July, K announced a partnership with insurance provider Anthem to let members see how doctors diagnose and treat similar people with similar symptoms for free (though they’ll be charged to chat with an actual doctor).

Computers were too slow and data too expensive to make AI practical at the time, but roughly three decades later, Pratt teamed up with investment firm TPG to help it identify a data analytics company to buy or invest in.

The company uses vast quantities of nontraditional data—like signals from cellphones, internet-of-things devices and street cameras—to issue hyperlocal “street-by-street, minute-by-minute” weather forecasts.

Its image processing technology, called Cortex, works with its own 3D camera, as well as a selection ofcheaper360-degree cameras, to let users create virtual versions of their space.The company’s leaning into the real estate market, showcasing how agents can use it to give 3D tours.

Beck, who spent more than five years as a pathologist at Harvard, wants to make it easier for other pathologists to diagnose diseases like cancer by using machine learning to more quickly and accurately analyze images of cells.

Its overhead cameras track individuals and items continuously (notably, its so-called entity cohesion doesn’t rely on facial recognition, which it says gives shoppers more privacy).

A lineup of cloud-connected security cameras equipped with AI-driven features like object and movement detection has driven growth at Verkada, whose cofounders are three Stanford computer science graduates and the cofounder of enterprise cloud company Meraki, which sold to Cisco for more than $1 billion.

Among the company’s wide-ranging list of clients are fitness club Equinox, the $1.1 billion Vancouver Mall and more than 500 school districts, which use the cameras for anything from monitoring student safety to tracking food deliveries.

SentinelOne CEO Tomer Weingarten says he and his cofounder started the company in 2013 because antivirus software at the time was “some flavor of bad, incomplete, ineffective, and /or painful to deploy and operate.” They spent the past six years figuring out how to make endpoint security (which focuses on data coming from laptops, phones, and other network-connected devices) smarter, training machine learning models to detect malware in files and running in applications.

“Until now, the most complex operations in manufacturing have been too difficult for blind and dumb robots to perform with the same precision and fidelity as humans,” says CEO Amar Hanspal, adding that advances in computer vision and machine learning have changed the game.

Upstart CEO Dave Girouard admits that most of the early team of former Google employees had no history in financial services when they came up with the idea to apply advanced data science to the credit process in 2012: Only the belief that the current system was antiquated and exclusionary.

By using data not typically found in a person’s credit history to find more nuanced risk patterns, Girouard says Upstart’s lending model has higher approval rates and lower interest rates than traditional methods, with loss rates that are “less than half” of those of peer platforms.

Former Oculus cofounder Palmer Luckey is back after his dramatic exit from Facebook (he has hinted that the company fired him from the virtual reality unit for his political views, which it denies) with a defense technology startup called Anduril Industries, founded in 2017.

It has contracts with the Marine Corps and UK’s Royal Navy, as well as with Customs and Border Protection for what has been described as a controversial “virtual border wall.” Following a report that it became a unicorn after a recent fundraise, the company confirmed to Forbes that it now has $180 million in total funding and a near-billion valuation.

Alexandr Wang’s data labeling startup Scale AI has gained so much attention from customers — particularly autonomous transportation companies, which need gobs of well-labeled data to train their systems — that he’s running a unicorn company before his 23rd birthday.

It pulls public data about a property to automatically answer many of the questions a typical insurer would ask, which means it can quickly dole out quotes, and pulls data from aerial images and smart home sensors to detect issues that could lead to claims in real-time.

Dataminr ingests public internet data, like social media posts, and uses deep learning, natural language processing, and advanced statistical modeling to send users tailored alerts.

Uptake CEO Brad Keywell says his company is in the business of making sure things work, “whether it’s the U.S. Army’s Bradley Fighting Vehicle, or the components that make up Rolls-Royce’s fleet of market-leading engines.” It’s brought in more than 100 industrial customers on its way to a $2.3 billion valuation.

trifecta of autonomy and transportation experts from Tesla, Uber, and Google came together to build Aurora, a self-driving car company that plans to sell its system to automakers instead of operating its own fleet (it currently has a deal with Hyundai to provide software for its future Kia models).

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