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Why these 6 hot AI startups are feeling the love from investors – TechGenix


The term artificial intelligence has been around for years. But it doesn’t just make for a cool concept behind a lot of sci-fi movies. In recent years, AI has emerged as a disruptor in multiple verticals from low-code driven by AI to automate developers’ tasks to robots in factories. As a growing market, AI has seemingly endless potential for being applied to various challenges faced by organizations large and small. Hence, it’s no surprise that AI startups are being noticed by investors who are looking to take advantage of this swiftly growing market. In 2018, venture capitals funded a record $9.8 billion in AI startups — that’s 10 percent of the total VC funding last year. So let’s take a look at some of the hottest AI startups that got funded in the last year.

1. HyperScience

This New York-based startup has recently raised $30 million in series B funding led by the Stripes Group. HyperScience is a machine learning company that was founded in 2014 and that operated in stealth till 2016. HyperScience helps companies across various sectors like health care, financial services, and insurance automate data entry processes and cut costs related to manual data entry. Manual data entry is expensive, slow, and erroneous and HyperScience can help companies transcribe human readable documents into machine readable data via automation. It ultimately helps offices cut costs and get more accuracy in data entry at greater speed. The recent funding has brought HyperScience’s total funding to $50 million. HyperScience plans on using this funding to grow its team while improving and updating its product further and focusing on sales and marketing.

2. Quid

When this San Francisco-based startup was founded in 2007, it went by the name of YouNoodle until 2010 when it got rebranded to Quid. In October 2018, Quid raised $37.5 million in series E funding led by REV Ventures, the investment arm of RELX Group, which contributed $10 million in this funding round.

Quid’s software ingests data from social media like Twitter, company websites, and news databases like LexisNexis. It analyzes the data and provides insights like trends in public opinions and changes in the company. Quid’s software is used by various communication agencies and management consultancies. Quid prices it’s subscription at $250,000 per year. Quid helps customers make sense of large amounts of unstructured data. Its clientele includes large global organizations like Hyundai, Microsoft, and the Boston Consulting Group.

3. Domino Data Lab

Domino Data Lab is a leading data science company that provides a model management framework. Domino believes that businesses require a dedicated platform for creation and management of predictive models. This platform should be separate from a software development platform as predictive models are an ongoing process by data scientists to get insights into trends and help companies work towards evolving and growing at a faster pace. Predictive models are created based on previous models and keep on changing. Domino’s customers include Easyjet, Allstate, Dell, and Monsanto.

Domino raised capital of $40 million from series D funding in August of last year. It plans on using this funding to help deliver new data science products, acquire new talent, and attain global expansion. Domino will also work on strengthening its strategic partnerships with SAS and AWS.

4. Alation

Alation is the answer for employees who are looking for some piece of data to make a day-to-day decision, but who do not know where it could be within a large amount of enterprise data split in multiple databases. Alation uses machine learning to automatically organize data in a single repository called the data catalog. This makes it easy for anyone to search the data that they are looking for without having to query various databases and schemas. It uses out-of-the-box connectors to connect to various sources like Oracle, Redshift, and Tableau among others. Users can simply use the data catalog to get the data they are looking for. Alation acts as a search engine for structured data. Users can enter keywords and Alation provides them with the data they are looking for. But that’s not where it stops. It provides suggestions based on its search logs. Think of it as Google for enterprise data.

Founded in 2012, this Redwood, Calif.-based startup has come a long way. With the recent series C funding of $50 million it has raised a total capital of $82 million. This funding round was led by Sapphire Ventures. Alation plans on doubling its work force with this investment and also funding research into machine learning initiatives.

5. Atomwise

This San Francisco-based startup has raised $45 million in a series A funding round last year, which was led by Monsanto Growth Ventures. Atomwise’s software uses deep learning to analyze molecules through simulation that eliminates time taken by researchers to synthesize and test compounds. Atomwise is running over 50 different molecular discovery programs. Atomwise screens up to 10 million compounds each day. Atomnet by Atomwise uses accumulated data about biochemical interactions to discover molecules that help prevent diseases while also studying their toxicity and their reaction with the human body. Atomwise also works on producing better fertilizers.

Atomwise has partnered with various pharmaceutical firms, biotechnology companies, and university research labs to work on developing drugs for cancer among other diseases. Using its latest funding, Atomwise wants to scale up and increase its workforce.

6. DataRobot

This Boston-based startup helps organization by providing them a faster way to use AI and machine learning. DataRobot helps automate work done by data scientists by making it easier for employees, both skilled and unskilled, to develop predictive models for boosting decision making. It’s an attractive offering for companies that want to grow using AI. DataRobot understands the lack of data scientists and helps in providing a substitute that works wonders for businesses of varying sizes.

DataRobot has raised capital of over $224 million in total. It plans on using its latest funding to address the ever-growing demand for its proven approach to automating data science solutions and to expand its portfolio. This latest funding of $100 million in series D last year was led by Meritech and Sapphire Ventures. DataRobot wants to further improve its offerings and it aims for a global expansion.

AI and AI startups: Not a passing fad

AI has matured in the recent years. It has been adopted by more businesses while startups keep coming out of nowhere with newer, more interesting solutions. Funding into these AI startups has seen a sharp incline recently. This surge is a clear testament to the rising popularity of AI and investing in AI startups. But even though the funding has increased, the number of deals in AI has decreased. This clearly shows that investors are now drawing distinctions between haves and have-nots. Investors are strategically investing in startups they deem as winners. Seed round deals have fallen from 39 percent in 2017 to a mere 30 percent in 2018. AI startups are overcrowding at the seed stage and that has led to increased competition.

With all the varied applications, AI is not a passing fad, but is set to permanently change the way humans interact with and glean value from data. This just shows how AI is a force to be reckoned with and businesses that pass up the chance to adopt AI are sure to be missing out in the future.

Images: Pixabay


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