DeepSee, a leading provider of Knowledge Process Automation solutions, today announced that it has been recognized in the Gartner “Emerging Technologies and Trends Impact Rader: Artificial Intelligence” report (Gartner subscription required). DeepSee was recognized as a sample vendor in the Composite AI category of Gartner’s report.
“Gartner has always been on the forefront of emerging technologies and market shifts, and we’re excited to be included in this report,” said Steve Shillingford, President and CEO of DeepSee. “While the AI hype is pervasive and probably peaking, DeepSee is all-in on the coming wave of consolidation – that is, just making it work in the day-to-day of business. We fundamentally believe in the value of data science, in as much as it solves practical business problems. The rapid innovation curve in AI has accelerated the demystification of ML and NLP and reduced the hurdles for line-of-business folks to achieve tangible ROIs here and we think DeepSee allows both the scientist and the analyst a better platform for getting their jobs done.”
The Composite AI category identified by Gartner refers to “the combined application of different AI techniques to improve the efficiency of learning, and ultimately to much more efficiently solve a wider range of business problems.”
Identifying the market trend toward multilayered AI solutions, Gartner’s experts warn, “The days of singular AI techniques are coming to an end. Software and service providers that cannot provide solutions combining multiple AI techniques through composite AI approaches will quickly find themselves at a disadvantage compared with those that can. The introduction of composite AI techniques, even within existing products, will have a profound impact on their capabilities.”
“We believe there are targeted and valuable insights and actions to be gained from rich unstructured data employing a myriad of NLP techniques,” said Bryan Sparks, Chief Technology Officer at DeepSee. “The solution we perceived integrates extraction and digitization of unstructured data types, supports the application of proprietary and open source AI models, and provides a pipeline to deliver business insights to the right systems for immediate action. And that’s exactly what we’re delivering now for our flagship partners and new customers in sectors like Capital Markets, Insurance, and Federal Contracting.”
The report highlights the timeliness of this composite approach, noting “The latest COVID-19 crisis and the advent of ‘small data’ problems have accelerated the investment in composite AI capabilities, giving its adopters a competitive advantage. This acceleration is accompanied by an influx of capital in this space, as well as a growth of organizations adopting those techniques out of necessity.”
Additionally, the report notes, “Many business problems require the ability to unveil unknown knowledge or patterns held within a large amount of data; capture known knowledge (know-how or compliance rules) in a structured manner; and find optimal combinations of resources given a number of constraints in a given amount of time. The respective AI techniques to be combined to address those issues are machine learning, rule-based systems and optimization techniques. The result of combining those various techniques (among others) is the delivery of a composite AI system.”
