Innovate Articles

AI Aids for Patent Prosecution - Product Review

Henry H. Perritt, Jr.

Introduction

Patent search and drafting of patent applications are good uses for generative AI, popularized by Chat GPT. The subject matter is well defined, and the publicly available database of patents and patent applications is enormous, facilitating good machine learning with large language models used by Chat GPT and its competitors.

A half-dozen vendors are deploying generative AI for patent prosecution: Dolcera’s IP Author (ipauthor.com), Rowan Patents (rowanpatents.com), Qatent (qatent.com), DorothyAI (www.dorothyai.com/products), davinci (www.getdavinci.ai) and XLScout.ai. Of these, Rowan Patents and IP Author are the most useful. Chat GPT itself can play a useful role. Davinci requested that it be excluded from this review.

What value do they add?

IP Author and Rowan Patents are ready for serious pilot projects in patent practices, and they have quite different strengths and weaknesses. IP Author’s integration with prior-art search capability is a considerable advantage, and it generates useful first drafts of all the elements of a patent application. Rowan Patents is a productive partner throughout the process of writing a patent application, but it offers limited assistance with prior art search.

Neither product can understand an invention; no AI technology can do that. Both can, however, tag phrases as concepts, and thereby relate them to other parts of the application. Nothing within the foreseeable future will allow a computer program to examine a model or watch a demonstration and describe what's inventive about it. So it always will be essential, as it is with all these products, for a user—inventor or patent lawyer-- to provide some kind of starting point describing the invention—a brief disclosure, draft claims, or drawings.

IP Author can generate draft claims; indeed vanilla GPT4 can do that if supplied with a simple description. Rowan Patents is much more interactive than IP Author. IP Author is more of a black box. With any of the products, a skilled patent lawyer will have to pay close attention to claims language.

An ideal implementation would use IP Author to come up with an initial draft, and then input that draft into Rowan Patents for managing drawings and the editing process.

Qatent is worth following, but it not ready for any serious implementation. The publicly available version of ChatGPT does a good job of drafting “Field of the Invention” and “Background of the Invention” sections when given a relatively simply Abstract section as a prompt.

Detailed capabilities

Both IP Author and Rowan Patents understand the structure of a patent application and organize pre-written material appropriately. IP Author concentrates on generating draft language through generative AI; Rowan Patents concentrates on managing terms and references according to MPEP standards. Provided with a brief description, IP Author drafted two independent claims and eighteen dependent claims in approximately 120 seconds. The user could edit the claims directly in a window to modify the invention, or to save the claims to draft a complete patent application. The software generated figures including a fairly detailed but primitive flowchart and a drafted a detailed description of the figures. The twenty-two page draft of the complete application could be downloaded in Microsoft Word .docx format.

Working from the same brief description, IP Author displayed prior art search results.  Each item of prior art had a graph rating similarity, along with brief paragraphs summarizing points of similarity and difference. The prior art identification and summary easily was downloadable in .docx format.

Dolcera’sIP Author’s work product was not perfect. It got the sequence of steps wrong in the flowchart. In another run, providing claims language along with a brief description confused it, triggering an endless loop. It produced claims language that interspersed system claims with method claims, repeated limitations in the independent claims, and expressed dependent claims in terms of the wrong independent claim. At one point, it hallucinated and produced drawings and associated detailed descriptions for an entirely different invention in a completely different field. Restarting the software fixed the problem.

Rowan Patents accepts claims, drawings, or brief descriptions as starting points. A user can begin by importing a Word file, in which case the system parses it and inserts portions into the appropriate sections of the Rowan patent. AI is just one small component of the software suite, which has been in use by the patent bar for a number of years. The program concentrates on defined data objects, such as claim terms, definitions, part numbers, and figure references. Once terms have been tagged, the system flags every instance of each term and provides a red warning for each term in the claims that does not also appear in the specification and in a drawing.

A user can enter text into defined windows, create drawings with provided tools, or import an existing .docx file by opening the entire file or by dragging and dropping components of it into the appropriate windows. A user can download a published patent or patent application, convert it to a .docx or to an .rp file, and cut and paste portions, editing them into a Rowan application.

One then can define new terms and parts by highlighting them and thereafter edit them. Edits propagate throughout the file. One can import an image, such as a drawing created by a commercial artist and apply numbers to it. One can import particular .pdf pages from a patent publication, crop them, and cover up existing elements such as numbers with new ones.

Rowan has a complete suite of drawing tools, including flow chart tools. It allows auto numbering using defined terms with point and click. It can auto generate flow charts and other figures. Using these tools, a user can generate a set of drawings more than adequate for initial submission to the patent office.

Initial implementation includes the ability to designate specific text in the draft patent application and then select from options of pre-built prompts for actions on that selected text. For example, selecting specific terminology provides options to define or describe that term. Selecting an entire paragraph (e.g. a claim) provides options to summarize that content. 

An optional bioscience module can keep track of DNA sequences.

The product has limited prior art search features through its “launch analytics" feature. This feature breaks a completed patent application into pieces, and send the pieces back to Rowan servers. Then gives the user an option whether the user wants to see search results and flags items of prior art that might present 102, 101, 103, or 112 difficulties. Does not, unlike IP author, summarize similarities and differences. Rowan does not keep copies of an application submitted for its analytics module.

Rowant Patents is harder to use than IP Author because navigating around the different Rowan modules is not intuitive and the choices in each module are confusing. Two very detailed instruction manuals are available, however, which help when a new user gets stuck. As with any full-featured software product, use would become intuitive after a few hours’ experience.

Qatent generated reference list of 31 nouns and gerunds from submitted description and claims. The figures it generated were garbled and the flow chart was generic. The brief description of drawings was generic with things like “Figure 4 shows Block Chart 2.” The claims were repeated almost verbatim in the specification’s detailed description. Grammar and style were atrocious, with meaningless terms like triplication, performant, conductive, operative, and performative scattered throughout the description.

DorothyAI is only a search engine, with no drafting capability advertised. It is advertised as “directly compar[int] the text of any document, such as inventions disclosures, patent claims, abstracts, product data sheets.”

Confidentiality

IP Author and Rowan Patents take secrecy and security seriously. Neither puts user provided information or software generated drafts into the Cloud, and every external exchange is encrypted.

Pricing

Dolcera offers three pricing options for IP Author: $499 per month per user for an unlimited number of inventions, including prior art search; $199 per response for office action responses, and $1499 per user per month for patent drafting, image-based claim generation, prior art search, and office action response.

Rowan offers flexible per-seat pricing, at roughly $500 per seat per month. A license for an attorney includes support staff without further charge.

Recommendations

Both the Dolcera and the Rowan products are ready for deployment as production elements in patent prosecution workflow--Dolcera’s IP Author at the threshold of a new application, Rowan Patents as a wingman throughout the application drafting process.

Generative AI technology is still trying to find a productive place in the legal world. Identifying useful work cases requires experienced practitioners to work with the technology developers and vendors to refine application concepts and product features.

Once a practice reaches agreement on a co-development relationship with a vendor, it should use the vendor’s product on actual patent applications and be rigorous in collecting data to compare lawyer and support staff time required without the products compared to time required with them. Ideally, this would involve time and motion studies identifying particular timekeepers and then attaching their hourly rates to the hours expended. 

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The views and opinions expressed in these articles are those of the authors and do not necessarily reflect the views or positions of AIPLA.