Machine learning and the Alice test

The Supreme Court did not delimit the precise contours of the abstract ideas or inventive steps. Instead, it asks to follow the examples set by the court system.

The lack of a definitive rule and the presence of prior cases as the central guidance to evaluate and understand notions such as abstractness or inventive steps suggest that machine learning can be a proper tool to help model and apply the Alice test.

The engine behind 101 Eligibility Analyzer is trained on the prior litigated cases to learn from them and use them as instructive examples to predict the outcome of the new cases.

A dependable tool for a volatile law

The judicial interpretations of abstract ideas and inventive steps have been quite fluid and changing over time. A new case could invalidate a previously valid patent overnight.

Stacks regularly updates its data and retrains its models with the latest judicial decisions to deliver the newest interpretation of the Alice test. Therefore, Stacks API can help users re-evaluate an entire patent portfolio in seconds and stay up to date.

Who should use this and why?

IP owners, in-house counsels, investors, IP traders and other stakeholders because they need to evaluate their IP portfolio and avoid expensive outsourcing.

Patent law practitioners because they have to navigate the landscape with the latest and most relevant updates of the law quickly.

Who should use this and why?

• New patent applicants who want to understand the prior art.
• Product managers because they need to discover any overlap between their product lineup and competitors' patents.
• IP owners who need to discover who is infringing their patent.
• Investment and financial institutions because they must assess the freedom-to-operate of a company or audit a product or a patent portfolio.

Advantages

• Perform IP research at scale quickly and cheaply.
• Stay on top of your company's patent portfolio.
• Monitor and keep track of new patents that could affect your business.
• Get the right results fast with advanced deep learning and natural language processing technologies.

Language agnostic engine

The use of obscure language within patent claims is widespread. So a conventional search engine that only picks up the textual similarity between a query and claims cannot do justice to users. Infringement Research API understands and measures technological similarity regardless of terminology. Provide an invention or product description, and get a list of claims that overlap with the description technology-wise.

Extensive research with simple steps

With Infringement Research API, you can run an in-depth, extensive IP analysis with a few clicks of a button. For example, analyze if thousands of product descriptions infringe an extensive patent portfolio quickly and easily.