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As a result of pandemic headwinds and the general trend toward automation, the industrial sector is increasingly piloting AI technologies across different lines of business. According to a Deloitte survey on AI adoption in manufacturing, 93% of companies believe that AI will be a pivotal technology to drive growth and innovation in the future. Illustrating the transformation, a McKinsey report found that 15% of manufacturing companies now use AI to optimize key areas of production such as yield, energy, or throughput optimization, up from 9% in 2018.
But stumbling blocks stand in the way of successful AI deployment in industrial applications. For example, Chinese companies responding to the above-mentioned Deloitte poll said that 91% of their AI projects failed to meet expectations either in terms of their benefits or time invested. Among the biggest obstacles cited were infrastructure limitations, poor data collection practices and quality, a lack of engineering experience, and excessively large project scale and complexity.
AI-focused consultancies have emerged recently to assist industrial as well as oil and gas, renewables, financial services, transportation, and government organizations in implementing AI technologies. Fractal Analytics, Tata Consultancy Services, Wipro, Tredence, LatentView, and Mu Sigma occupy a growing category of “AI-as-a-service” companies that work with enterprises to develop AI solutions customized for their organizations. So does SparkCognition, an Austin, Texas-based firm that uses AI to analyze, optimize, and learn from customers’ data to predict future outcomes, optimize processes, and ostensibly prevent cyberattacks.
In a show of the market’s strength, SparkCognition today announced that it raised $123 million in series D funding at a $1.4 billion valuation led by March Capital, Doha Venture Capital, B. Riley Venture Capital, AEI Horizon X, Temasek, Alan Howard, and Peter Löscher, bringing the company’s total raised to $300 million. The financing follows a record year of growth for SparkCognition, with revenue increasing 90% year over year and booking climbing by five times.
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Developing AI solutions
SparkCognition was founded in 2013 by Amir Husain. Husain previously launched Kurion, which created branded web portals for companies including Barnes and Noble, Dun & Bradstreet, and financial services institutions. He then led development of desktop computing products at ClearCube before joining virtualization services company VDIworks as CTO.
“[T]he pandemic has heightened our customers’ understanding of the value AI can deliver. In the face of supply chain uncertainties, fluctuating demand for resources like oil and gas, and increased remote work, it is never more critical to have advanced analytics predicting failures and cyberattacks before they occur, flagging operational inefficiencies, and identifying opportunities for increased production. This ultimately impacts our customers’ bottom line, helping them see business growth even in uncertain times,” Husain told VentureBeat via email.
SparkCognition provides a range of services developed to overcome particular data science hurdles in organizations. For instance, the company’s Darwin tool abstracts away many of the steps in developing and maintaining AI models, including data preparation and cleansing. Husain claims that Darwin can uncover problems like missing data while suggesting solutions to problems in an AI training dataset, such as malformed or missing data. Darwin can also ostensibly deliver “explainable” model results that spotlight important aspects of a dataset, he says.
On the cybersecurity side, SparkCognition offers DeepArmor, which leverages AI to attempt to mitigate executable-based cyberattacks. Meanwhile, the company’s DeepNLP service automates workflows of unstructured data to simplify tasks like information retrieval, document classification, and analytics. SparkCognition’s SparkPredict and Ensemble are AI-powered asset management and predictive maintenance platforms, built to detect suboptimal production yields and equipment failures proactively. Rounding out the product portfolio is Maana, which aims to encode organizations’ institutional knowledge, and an AI-powered market trading platform called Orca.
“Enterprises are faced with data overload, and 90% of data available is unstructured, which traditionally requires an extraordinary amount of manual effort to sort through and extract insights … [B]ut echnologies like the solutions we offer use machine learning and natural language processing to expedite that process significantly,” Husain said. “We take an end-to-end approach, leveraging technology like artificial intelligence, machine learning, deep learning, natural language processing, and knowledge representation. We deliver these solutions in a user-friendly interface that quickly and clearly provides insights and alerts when a process or asset needs attention.”
Three-hundred-employee SparkCognition positioned itself for growth last year, acquiring three companies and expanding into the financial services, maritime and renewable energy markets. According to Husain, SparkCognition — which has 65 customers — helped a major power generation company spot an anomaly that “enabled critical event detection a month in advance,” helping that company to avoid costly repairs. It also worked with a beverage manufacturer to address water waste and leaks, Husain said — reducing consumption of the resources throughout the manufacturing plant.
“This additional capital will enable us to deepen our subject matter expertise, enhance our patented portfolio, and accelerate the diversity of problems we solve for customers, maximizing their return on investment,” Husain continued.
But surveys show that organizations struggle to derive value from their AI deployments — representing an existential threat to SparkCognition’s business. For example, a 2018 report from 451 Research found that the majority of AI early adopters have failed to define key performance indicators around their AI and machine learning initiatives and encountered technical limitations while operationalizing data.
In more sobering metrics, 76% of organizations in a 2020 PricewaterhouseCoopers-sponsored survey reported barely breaking even with their investments in AI capabilities. Despite the fact that 80% of executives said they believed AI will fundamentally change their business, only 6% had AI initiatives scaled across the enterprise.
“Organizations are relying on existing talent and processes more oriented to software development than to the dynamic nature of AI. Many may underestimate the effort and investment they need in order to see returns,” a piece in the Harvard Business Review reads. “And many organizations may lack the governance structures to monitor AI effectively.”
Still, Husain believes that SparkCognition is primed to make a change once the proceeds from the series D are put toward planned marketing, sales, and R&D efforts. To his point, the broader AI market shows signs of accelerating, not slowing, with 39% of large companies planning to invest in AI services as of 2020.
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“We’re seeing quite a few challenges facing our customers across industry. These include aging and failing assets, climate change and net-zero initiatives, emerging cyberthreats to IT … infrastructure, an aging workforce and consequential skill gaps, and data overload,” Husain added. “To address these challenges, we encourage businesses across all of our key industries to invest in AI solutions that allow customers to gather insights to prevent unexpected downtime, maximize asset performance, and ensure worker safety, all while avoiding zero-day cyberattacks on essential IT … infrastructure.”
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