The scaling of machine intelligence technology in the enterprise continues apace with another successful venture funding round reported by a cognitive computing startup.
CognitiveScale of Austin, Texas, said on Tuesday that Intel Capital and Norwest Venture Partners led a Series B funding round that garnered $21.8 million. The startup launched nearly two years ago by IBM veterans said it would use the cash infusion to expand its product portfolio and global sales as demand grows for cognitive applications based on machine learning.
Representatives from both venture funds will join CognitiveScale’s board, the startup added.
“This funding will accelerate our mission to bring scalable, practical [artificial intelligence] to the enterprise,” Manoj Saxena, executive chairman of CognitiveScale noted in a statement. The startup emerged from stealth mode in October 2014. Saxena previously served as the first general manager of IBM’s Watson cognitive computing unit.
The company’s cloud software is intended to apply machine-learning techniques to business processes. The startup claims more than 60 patents filed around its Deep Cognition Engine described as a set of “industry specific” AI algorithms that can adapt to changing user and market conditions. CognitiveScale also claims a growing roster of customers in the financial services, healthcare and retail sectors.
CTO Matt Sanchez, who previously led IBM’s Watson Lab, founded CognitiveScale. CEO Akshay Sabhikhi also worked on healthcare applications at IBM before joining the startup.
CognitiveScale and other startups are attempting to catch the wave of AI technologies that use machine learning to predict by using ever-larger volumes of data, especially the torrent of unstructured data culled from social media and other sources. With that in mind, Intel Capital said it hopes to leverage the technology to complement efforts such as optimizing Spark analytics for Intel-based platforms.
The company currently offers two machine intelligence platforms designed to crunch multi-structured big data and disseminate results across enterprises with an eye toward eventually supporting mission critical company functions. A customer-facing platform operates at the business “edge” to glean business intelligence such as consumer preferences. The other platform functions as an internal tool that deploys “self-learning autonomous processes” while providing enterprises with “contextual insights” about specific markets, CognitiveScale said.
The startup further claims its machine intelligence tools learn from new data and customer interactions to deliver “advice that accounts for dynamic changes in goals, preferences, and the business environment.” The cognitive cloud tools are currently available through IBM as well as Amazon Web Services and Microsoft Azure cloud infrastructure.
Along with IBM and AWS, the company also is working with partners such as Deloitte Consulting to fine-tune is business process applications as banks and other financial institutions embrace big data, analytics and cognitive computing.
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