Analytics startup Unsupervised raises $35M to spot patterns in enterprise data
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Boulder, Colorado-based Unsupervised, a big data analytics company leveraging AI to find patterns in business data, today announced that it raised $35 million in a series B round led by Cathay Innovation and Signalfire. Unsupervised says that it intends to use the funding to hire additional employees as it continues to develop its platform.
Most enterprises have to wrangle countless data buckets, some of which inevitably become underused or forgotten. A Forrester survey found that between 60% and 73% of all data within corporations is never analyzed for insights or larger trends. The opportunity cost of this unused data is substantial, with a Veritas report pegging it at $3.3 trillion by 2020. That’s perhaps why the corporate sector has taken an interest in solutions that ingest, understand, organize, and act on digital content from multiple digital sources.
Unsupervised claims to accomplish this by analyzing unstructured and structured datasets to arrive at insights “without ignoring the long tail.” The company automates data science processes including preparation and prioritization, making predictions on data in industries spanning transportation, supply chain, ecommerce, and sales and marketing.
“We’re seeing a shift in the market where customers are seeking out analytics and AI platforms that don’t just do simple reporting — they reveal opportunities to change the business. BI and traditional AI is great for probing handfuls of known problems, but when you’re really trying to understand what’s happening you need to investigate beyond known issues,” CEO Noah Horton told VentureBeat via email. “This is where unsupervised learning is uniquely valuable. COVID really revealed the need for what we’ve built and this round will help us expand our footprint faster.”
Unsupervised says that its AI can identify statistically significant patterns that highlight the differences across subgroups within the data. Using a technique called unsupervised learning or self-supervised learning, Unsupervised’s systems can generate labels from data by exposing the relationships between the data’s parts. That’s as opposed to traditional, supervised AI systems, which require annotated datasets in order to learn patterns and make predictions.
Above: Unsupervised’s web dashboard.
For example, in the supply chain domain, Unsupervised’s AI can ostensibly look at the nuances of the local economy, logistics site, employee details, and shipments and inventory to spotlight areas with excess or insufficient supply. On the finance side, Unsupervised can drawn on databases to find fraud schemes and spot financial trends like where people are willing to spend versus save. The technology even has applications in health care, Unsupervised says, where it can reveal opportunities to minimize the time spent on administrative tasks.
Unsupervised’s platform presents AI-discovered patterns to customers for review in a web dashboard. Teams can track the performance of these patterns over time, and the AI system learns from what’s prioritized and acted on to continuously improve the insights.
Momentum in the market
Unsupervised isn’t disclosing many customers at this point. That said, the company volunteered that it has “a number” of Fortune 500 customers using the product, including teams at ADP, Disney, and Coatue.
“Unsupervised’s customers use the platform for multiple use cases. The average customer is using the platform across three or more use cases. Some customers are supporting as many seven use cases with Unsupervised at one time,” a spokesperson told VentureBeat.
In its recent Augmented Analytics Is the Future of Analytics report, Gartner predicts that by 2021, “augmented analytics” like Unsupervised’s will drive new purchases of analytics and business intelligence, as well as data science and machine learning platforms. Assuming this comes to pass, 75-employee Unsupervised’s prospects in the $168.8 billion business analytics market look bright — even in the face of competition from companies like Outlier.
“Most companies recognize that data is the new ‘gold’ but still struggle to derive meaningful insights given the deluge of siloed data, both structured and unstructured, across organizations — exasperating teams that are already understaffed and overwhelmed,” Unsupervised cofounder and CEO Horton told VentureBeat. “However, Unsupervised’s unique approach to ‘AI-augmented analytics’ has the potential to be a game-changing tool. It is disrupting the entire process by ingesting data from everywhere and automating the time consuming, tedious portions so users can quickly draw the most interesting insights that are revenue-generating and actionable. We’re honored to support the company on their journey, which very well may usher in a transformation of big data and decision-making in the enterprise.”
Eniac Ventures and Coatue also participated in the company’s latest funding round. It brings Unsupervised’s total raised to over $55 million following a $12.8 million series A round in August 2019.
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