DigitalOwl raises $20 million Series A for AI medical analysis platform
The Israeli startup’s platform reads, summarizes, and analyzes medical records for insurance and legal companies to help them better combat fraud, underwrite new plans, execute claims, and build strong legal cases
15:0026.01.22
DigitalOwl, which uses Natural Language Processing (NLP) technology to analyze and summarize medical records, announced on Wednesday a $20 million Series A round led by New York-based global private equity and venture capital firm Insight Partners, with participation from existing investors Ibex Investors and Fusion VC. The round follows the company's $6.5 million Seed announcement in February 2021.
DigitalOwl co-founders Yuval Man (right) and Amit Man. Photo: Ron Shushan
Tens of millions of medical records every year are manually reviewed by highly trained professionals at insurance companies in order to make important decisions for their companies and customers. The sheer volume and complexity of information requires a slow and methodical review of every page, often taking days at a time. DigitalOwl addresses this issue by reading, summarizing, and analyzing medical records for insurance and legal companies to help them better combat fraud, underwrite new plans, execute claims, and build strong legal cases.
DigitalOwl co-founders Yuval Man (right) and Amit Man. Photo: Ron Shushan The company was founded in 2018 by two brothers, CEO Yuval Man, a former personal injury lawyer, and CTO Amit Man, an expert in artificial intelligence. DigitalOwl currently employs around 50 people in Israel and the U.S.
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The average medical record holds more than 44,000 words entailing more than 2,900 medical extractions, data points such as procedures, conditions, and medications. DigitalOwl’s technology solution extracts over 17,000 medical data points from a variety of different conditions, procedures, and medications including cancer, heart disease, accidents, orthopedic surgeries, diabetes, arthritis, hypertension, and brain injuries, with greater than 95% accuracy.
“Our solution is a proprietary Natural Language Processing technology that extracts information from hundreds or thousands of pages of scanned medical records in minutes and presents that data chronologically, allowing users to search and filter by condition, date, body part, body system, and provider,” said Amit Man, CTO and Co-Founder. “The DigitalOwl system is capable of extracting twice as many meaningful medical data points as any human-enabled solution, at a fraction of the cost.”
