12 No-Code Platforms for Some DIY Machine Learning
Only 25% of organizations are using artificial intelligence (AI) in their businesses today. Why? Custom AI-enabled solutions are expensive to build, as talented data scientists are a hot commodity today and don’t come cheap. Top performers can easily command over $250,000 in annual salary, which seriously makes us question the money we
wasted invested in getting our MBAs. Not to mention, it can take months or even years to implement. CTOs are understandably suspicious of the latest buzzword du jour, so you need to show results fast.
Enter the no-code movement. No-code is the philosophy that the professionals who didn’t study software engineering in college should be given the power to build software. Then we can call them “citizen developers” and eliminate a few back-office positions in Mumbai. Using drag-and-drop interfaces, anyone from a tech-illiterate manager to a tween Instagram influencer can use the most sophisticated tools on the planet. There are now plenty of vendors talking about democratizing AI using no-code platforms, while anyone who has ever worked in software development might question this claim.
We’ve talked about no-code and low-code platforms before, but no-code development platforms for AI are a relatively new outcrop of the movement. Since leveraging customized AI is expensive, companies are beginning to pick up on lower-cost options that allow their technologically challenged employees to deploy these no-code options for solving boring, mundane tasks like data entry, data processing, predictive analytics, and keyword search. Some previous companies in this growing space of no-code AI platforms we’ve covered in the past include DataRobot, Super Annotate, and Rapid Miner.
In the last year, investor interest has been growing, as enterprises across all sectors are realizing the value of no-code AI platforms, which can solve real business problems quickly, efficiently, and with fewer employees. Let’s take a look at 12 startup companies making a splash with no-code AI platforms.
No-Code AI Platforms for HR and Customer Service
Founded in 2018, BRYTER is headquartered in Berlin and has brought in $89 million, the majority of which came in the form of a $66 million Series B that closed just this month. BRYTER helps companies build virtual assistants, chatbots, self-service tools, and other applications, something they refer to as “service automation.” The company’s platform provides a scalable compliance solution for services within legal, tax, HR, and security functions, which are traditionally manually performed and not easily scalable. If you’ve served hard time in a corporation, you’ll know that you frequently interact with departments where sensitive information is exchanged. BRYTER makes these transactions automated and secure.
Founded in 2014, San Francisco Bay Area-based Ushur is building a no-code AI platform for businesses to augment customer service functions and has received $42 million to further that cause. The company helps enterprises build conversational AI for customer engagement, emails, and of course, deflection. Ushur is focusing its attention on the insurance sector, which is definitely low-hanging fruit for automated solutions that will improve customer relationships. The startup has plans to expand in the financial and telecoms industries after seeing a spike in demand for its services during The Rona.
No-Code AI Platforms for Financial Services
Accern is a New Yawk-headquartered startup founded in 2014 with $19 million in disclosed funding. Accern serves as both a marketplace of unstructured data, sourced from financial news, subscriptions, reports, and social media, and as a service provider for AI-enabled tools to comb through that data and gain actionable investment insights.
The company offers more than 400 use cases, allowing users to quickly develop and deploy applications for their specific needs. Accern allows banks, insurance companies, and hedge funds to wade through oceans of financial data with accuracy and speed without relying on an expensive team of data scientists to build custom solutions.
Signzy is an Indian AI-powered fintech startup founded in 2015 that’s pulled in $12.6 million from the likes of Mastercard (MA) and other investors. The company is building out no-code AI platforms for the financial industry to reduce fraud. Most cases of fraud in banking occur at the level of human interaction with supposed clients. Signzy provides a simple platform for financial institutions to design automated systems that reduce human error. Use cases include secure digital contracts with biometrics, identity verification, and customer onboarding.
No-Code AI Platforms for Creatives
Founded in 2018, Runway ML is another New Yawk-based company that has brought in $10.5 million after a recent Series A round. Runway ML is applying the no-code platform strategy to provide companies with the tools to produce synthetic images and videos, edit content, and animate faces using the power of AI. Built for creatives, the company’s platform allows artistic professionals to harness machine learning to streamline their work.
For example, an animator can run a neural network built from Runway ML to create wireframes that’ll turn a human model into a 3D model. Runway ML’s product bridges the gap between the left-brained kids who graduated with a degree in software engineering degree and those who fled to art school.
Fritz AI, founded in 2017, is a machine learning platform for smartphone developers based in Boston. The startup has raised $7 million to help developers quickly build apps embedded with AI technology. Some examples of apps built using the Fritz AI platform include a healthcare app that searches for acne on your face, a farmer assistance app that detects crop diseases, and a photography app that superimposes images together. The platform has even been used to detect pizza in images, a very critical technology for anyone trolling Instagram for some free ‘za. The models offered by Fritz AI are pre-trained, which means you don’t need to provide your own big data sets.
No-Code AI Platforms for Predictive Data Analysis
Oregon’s own BigML was founded in 2011 to build a machine learning platform that helps companies sort through data libraries and make data-driven decisions across all industries. With $4.4 million in disclosed funding thus far, the BigML platform contains a library of machine learning algorithms that can read through massive amounts of data, organize data into complete datasets, and build data models.
Founded in 2018, MyDataModels is a French no-code AI startup that helps professionals take full advantage of their data through automated analysis, raising $4.2 million in disclosed funding to date. The company provides data extraction and analysis solutions with its main platform, TADA, which builds thousands of model algorithms and chooses one with optimal performance for the user’s particular dataset. In one particular use case, general practitioners fed symptom data from COVID-19 patients into the TADA platform to search for symptoms that were crucial.
The platform produced a model with 88% diagnostic accuracy in two weeks.
Founded in 2019, Berkeley-based Obviously AI has raised an undisclosed amount of funding from names that included NVIDIA (NVDA), and Sequoia. Obviously AI provides algorithms to users that can forecast revenue, optimize supply chains, and create marketing campaigns with a personalized twist. Using the company’s platform, an insurance company was able to predict which customers would be easier to upsell insurance. The company claims you can use their platform to predict just about anything.
No-Code AI Platforms for Document Analysis
San Francisco-based MonkeyLearn has raised $3.2 million so far to build a text analysis platform that uses machine learning to help businesses automate their workflows. MonkeyLearn’s platform provides users the tools to integrate AI-powered text analysis into applications that can conduct sentiment analysis, classify topics, and detect names, places, and organizations in a sea of unorganized text. Data in the form of a spreadsheet is provided to the algorithms as input, and then the magic happens. For example, it might help marketers figure out if customers hate their product from reviews, emails, and online comments.
Levity is a German no-code AI startup that’s raised $1.7 million in disclosed funding since its founding in 2018. The company has built a platform that creates solutions to deal with mundane, repetitive tasks that can eat up productivity. A few use cases include automatically verifying if documents are completed, categorizing service requests and email content, and analyzing text responses from surveys. And if the models built from the platform are unsure of the next step, they’ll ask you for the next move so it keeps the human in the loop and always gets better. Make sure not to say your social security number out loud.
Founded in 2017, San Francisco-based Nanonets pulled in $1.5 million from a Seed round that included Y Combinator to develop a no-code platform that allows businesses to build AI-powered applications for document processing. The AI gets trained on the mountains of unstructured documents routinely produced by companies to search for keywords or numbers. The goal is to eliminate the interns hired to laboriously enter data. The platform can be used to build solutions that scrape data from PDFs, hardcopy invoices, receipts, images, resumes, and ID cards, and transform them into machine-readable data.
While no-code AI platforms can’t completely replace a mercenary team of Stanford-trained computer scientists, they offer a powerful alternative for companies looking to do some of their own robotics process automation (RPA). No-code AI platforms put some of the most powerful technologies in the hands of every person for a monthly fee that’s less than a teenager’s cell phone bill. At least, that’s what the marketing brochures say.
While most no-code applications are still limited to canned sets of industry-agnostic functions, the depth and breadth of possibilities are growing as these startups continue to develop more sophisticated plug-and-play AI algorithms. Maybe one day we’ll have no-code options for building an entire company, employee-free, solely with the power of AI.
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