IP Law Daily, PATENT—D. Del.: Eligibility challenge to Aon Re machine learning patent fails, (Jul 16, 2025)

By Steven Melendez

A federal judge denied a motion to dismiss a patent suit, finding the patent was not directed to a mere "abstract idea."

A Delaware federal judge denied Zesty.AI, Inc's motion to dismiss a patent infringement suit brought by Aon Re, Inc., declining to find Aon's patent covered an ineligible "abstract idea" (Aon Re, Inc. v. Zesty.AI, Inc., No. 1:25-cv-00201-JFM (D. Del. July 15, 2025)).

Aon alleges Zesty infringes four similar patents—U.S. Patent Nos. 10,529,029, 10,650,285, 11,030,491, and 11,195,058—relating to computer systems that use machine-learning classifiers to analyze photos of buildings, spot features like roofs, and assess their condition. Machine learning classifiers "are computer software models that can evaluate input data and classify it into categories," according to the ruling.

The technology uses the results from the classifiers to evaluate a property' susceptibility to damage during disasters, used by insurers like Aon to assess risk and price potential coverage.

Zesty filed to dismiss the suit, arguing the patents claim ineligible subject matter, primarily discussing Claim 1 of the ’029 patent. That claim covers a "method for automatically categorizing a repair condition of a property characteristic.” The method involves receiving a user request, accessing an aerial image of a relevant property, extracting image features corresponding to a property characteristic such a roof shape via one machine-learning classifier, determining a condition classification for that physical characteristic using a second machine-learning classifier, and using the results of the classifiers to generate a condition assessment and risk estimate that is provided to the user.

Zesty argued that claim is "directed to the abstract idea of 'looking at aerial imagery to estimate risk" and simply applying "generic machine-learning technology to automate tasks traditionally performed by human inspectors," according to the ruling. The company claimed that's similar to other claims found ineligible for patent protection since they merely implemented human practices with conventional technology.

Aon contended that the claim's citation of two independent machine-learning algorithms "goes beyond merely automating existing practices with generic technology," according to the ruling. "Instead, Aon argues, this approach meaningfully improves the speed and efficiency of property assessments compared to prior computer-implemented techniques," according to the ruling.

Patent eligibility. The court applied a legal standard for patent eligibility developed by the Supreme Court in Alice Corp. Pty. v. CLS Bank Int’l and Mayo Collaborative Servs. v. Prometheus Labs., Inc. Under that standard, the court first determines whether the claim is in fact "directed to a patent-ineligible concept" like an abstract idea. If so, the court further considers whether the claims still contain an "inventive concept" that transforms the idea into a patent-eligible invention.

One consideration, according to the court, is "preemption"—whether the claim "effectively forecloses all practical applications of an abstract idea" and limits further innovation, a particular risk when claims "invoke computer technology in sweeping or generalized terms." That risk can be avoided when claims "recite more than a result-oriented goal or functional description" and "provide solutions in specific, non- conventional, or technical ways," according to the ruling.

In this case, the court ruled, the patent claim doesn't "broadly claim evaluating risk using imagery" but instead "recites a process with a distinctive structure" involving the two separate machine-learning classifiers using "pixel groupings obtained from digital images" and providing the condition and risk information to the user.

The two classifiers are important for efficiency and reliability, and the claim doesn't merely discuss using computers and machine learning to achieve a certain result, according to the ruling.

"Claim 1 is not particularly hard to understand; Aon does not pretend that it is," according to the ruling. "But intricacy must not be the principal measure of eligibility—why should elegant inventions be prejudiced? Claim 1 presents a targeted, technical solution to a specific problem and reflects more than a generic invocation of machine learning. Thus, it is directed to patent-eligible subject matter."

The Case is No. 1:25-cv-00201-JFM.

Judge: Murphy, B.

Attorneys: Pilar Gabrielle Kraman (Young, Conaway, Stargatt & Taylor LLP) for AON Re, Inc. Brian E. Farnan (Farnan LLP) for Zesty.AI, Inc.

Companies: AON Re, Inc.; Zesty.AI, Inc.

Cases: AINews Patent TechnologyInternet DelawareNews