DeepSee.ai raises $22.6m for its process automation platform
The AI-powered platform converts raw and unstructured business data into actionable knowledge
The round also saw participation from DeepSee’s existing investors, including AllegisCyber Capital and Signal Peak Ventures. The company will use the funds to “speed up product growth and expand to new verticals.”
“We established DeepSee to bridge the gap in between highly effective technology and line-of-enterprise, with adaptable solutions that empower our buyers to operationalize AI-driven automation – offering more rapidly, improved, and more cost-effective benefits for our customers,” said DeepSee.ai CEO Steve Shillingford.
DeepSee.ai claims its automation platform is different from conventional robotic procedure automation. Citing its procedure as “knowledge system automation (KPA),” the enterprise says its three-tier platform “mines unstructured facts, operationalizes AI-driven insights, and automates final results into authentic-time motion for the business.”
The first tier, DeepSee Assembler, ingests unstructured data and primes it for labeling, model review, and analysis.
A second tool, DeepSee Atlas, then uses this data to train artificial intelligence (AI) models that implement rules and logic for automating a company’s internal processes.
Realising the benefits of automated machine learning
How to overcome machine learning obstacles and start reaping the benefitsDownload now
The third tool, DeepSee Advisor, leverages text analysis techniques to gather cognitive insights so enterprises can evaluate how data impacts their business.
Until now, DeepSee.ai offered its solutions to insurance companies, the public sector, and capital markets only. The solutions helped with fraud detection, claims prediction and processing, and pattern recognition in agent audits.
The company now aims to expand to new verticals. “Using KPA, line-of-business executives can bridge data science and enterprise outcomes, operationalize AI/ML-powered automation at scale, and use predictive insights in real-time to grow revenue, reduce cost, and mitigate risk,” said Sean Cunningham, managing director of ForgePoint Capital.
“As a leading cyber security investor, ForgePoint sees the daily security challenges around insider threat, data visibility, and compliance. This investment in DeepSee accelerates the ability to reduce risk with business automation and delivers much-needed AI transparency required by customers for implementation.”
The ultimate law enforcement agency guide to going mobile
Best practices for implementing a mobile device programFree download
The business value of Red Hat OpenShift
Platform cost savings, ROI, and the challenges and opportunities of Red Hat OpenShiftFree download
Managing security and risk across the IT supply chain: A practical approach
Best practices for IT supply chain securityFree download
Digital remote monitoring and dispatch services’ impact on edge computing and data centres
Seven trends redefining remote monitoring and field service dispatch service requirementsFree download