Intraspexion owns a portfolio of seven (7) software system patents using Deep Learning. They include 120 claims and cover both risks to avoid and financial advantages to obtain.
Identifying general risk & providing early warning
On January 24, 2017, the United States Patent and Trademark Office (USPTO) issued Patent No. 9,552,548 to Intraspexion founder Nelson (Nick) Brestoff as the sole inventor for “Using Classified Text and Deep Learning Algorithms to Identify [General] Risk and Provide Early Warning.” A second "general risk" patent by the same title but with different claims bears the No. 9,760,850.
These patents, and the following patents, have been assigned to Intraspexion. Each patent may be found via the USPTO's website or by using Google Scholar (www.scholar.google.com).
On the basis of these "general risk" patents, Intraspexion's first product is a system to help corporate counsel identify the risks of specific types of lawsuits, of which there are many. With an early warning, corporate counsel can avoid lawsuits rather than manage them.
Early warnings for specific types of risk
On September 5, 2017, the USPTO issued Patent No. 9,754,205, No. 9,754,206, and No. 9,754,219 to Brestoff as the sole inventor for using classified text and deep learning algorithms to identify risk and provide early warning related to contract drafting defects, entertainment/publishing projects, and product defects.
Also on September 5, 2017, the USPTO issued Patent No. 9,754,220 to Brestoff and his son Jonathan R. Brestoff Parker, MD PhD MPH, as co-inventors for “Using Classified Text and Deep Learning Algorithms to Identify Medical Risk and Provide Early Warning.”
Supporting financial advantages
On September 5, 2017, the USPTO issued Patent No. 9,754,218 to Brestoff as the sole inventor for “Using Classified Text and Deep Learning Algorithms to Identify Support for Financial Advantage and Provide Notice.” This patent is similar to the others, but is for a different purpose: identifying a financial advantage to obtain (such as an R & D tax credit) rather than a risk to avoid.