Top 10 Ways PatentTech is Disrupting Patent Procurement

By Ian C. Schick, PhD, JD, CEO & Co-founder of Specifio (first posted on

A wave of new technologies is hitting the market with a specific focus on solving problems and inefficiencies in the patent procurement pipeline, from invention conception to patent issuance. This growing subset of LegalTech has come to be known as “PatentTech.” These new solutions are challenging the status quo of patent practice and becoming increasingly mainstream across the spectrum of law firms and in-house patent departments.

Two analogous technology disruptions in service industries include electronic spreadsheets in accounting[1] and computer-aided drafting in architecture[2]. In both cases, these disruptive technologies resulted in “a net positive for the industry with higher quality, higher efficiency, better access to services, and growth in the workforce”[3].

PatentTech solutions are wide-ranging, but generally fit into the following categories: document automation, process automation, and big data insights. Below is a breakdown of the top 10 ways in which PatentTech is changing how patent professionals and patent practices operate.

1. Invention harvesting: Ideation starts the patent process. Traditionally, patent attorneys often hold brainstorming sessions with engineering teams to identify potentially protectable inventions. Once identified, those inventions are assessed for business value, likelihood of eventual protection, and expected cost to pursue protection. This analysis then forms the basis for a comprehensive IP portfolio strategy. At least two companies– and Bright Marbles–are working in this space.

Automating this brainstorming process addresses strategic and practical aspects. Brainstorming automation can be informed by the prior art, specific competitor products, and the patent owner’s portfolio or the portfolios of their competitors, which can make the results highly-targeted based on business strategies. At the same time, automated ideation may offer more thorough mining via systematic and context-based approaches. Since the information gathered is in digital form, brainstorming automation should also force good IP inventory management. From a practical standpoint, being able to automate ideation eases friction with inventor/attorney scheduling and can even be performed asynchronously among inventors.

2. Invention disclosure: Once inventions are identified, the inventor must sufficiently convey the invention to the patent practitioner such that the practitioner can prepare a patent application that would enable one of ordinary skill in the relevant art to make and use the invention. One popular way of doing this includes having inventors complete a standardized invention disclosure form (IDF) covering the topics relevant to preparing and filing a patent application. Some companies, like ClearAccessIP and AppColl, have platformized this step in the patent procurement pipeline. These existing solutions seem focused on form-based approaches but are presented via a user-friendly web-based interface.

Indeed, anything that addresses friction in the disclosure process is a step in the right direction. However, invention disclosure could be one of the best areas of opportunity for future PatentTech solutions. For example, a semi-intelligent chatbot could certainly perform a more-than-cursory invention disclosure meeting that results in a completed, standardized IDF. The practitioner may still need to follow up with the inventor with some specific questions, but automating a majority of the disclosure process with a natural language interface accessible by the inventor anywhere, anytime would take a lot of pain out of the process and likely result in a higher volume of disclosures.

3. Prior art searching: Evaluating the relevant prior art is an important part of informing the decision of whether to file a patent and, if the answer is yes, determining the appropriate language and scope of the claims and specification. The goal of this exercise is to file patent applications with the highest chances of being allowed based on what is known about the prior art. Cutting out low probability applications and minimizing the number of office action cycles results in efficiencies enjoyed by all stakeholders–patent owners, practitioners, and the Patent Office.  

Several young companies, including Legalicity and DorothyAI, are automating patent search using AI. Automating this process, even if it’s just an initial screen of the prior art, can save hours of time for practitioners and professional searchers. In addition to speeding up turnaround on search projects, automation also makes it more feasible to do in-depth prior art analyses on a greater portion of a given portfolio.

4. Application drafting: The most time-consuming project in the patent procurement pipeline is drafting patent applications, which generally takes a skilled practitioner 20+ hours to complete. By segregating the judgment- and creativity-driven parts of patent preparation from the more mechanical aspects, automated drafting lets practitioners focus their talent on the truly high value-added components of the process. With intensifying cost pressure (see our prior post discussing revenue and cost trends in patent procurement), practitioners are turning to auto-drafting as a viable alternative to offshoring their drafting work.

A handful of rudimentary auto-drafting tools have popped up over the past year or so, mostly bespoke solutions developed in-house by drafting outsourcers and even by law firms in at least two cases. Fully- and partially-automated third-party drafting services, however, are now becoming available to the broader market. With Specifio‘s service, attorney-written claims are used to automatically generate a first-draft patent application with baseline 112 support. The idea, then, is for practitioners to bolster and finalize their auto-drafts ahead of filing with additional details and context around the invention.

5. Claim and spec proofreading: Sometimes small mistakes in patent applications can cost thousands of dollars to fix after the application has been filed. If a patent issues with certain errors in the text, it can even render the patent unenforceable or severely limit the scope of protection. As such, careful proofreading of the claims and specification is prudent (if not essential) ahead of filing the application.

While the rules are relatively simple, performing a thorough proofread by hand is tedious, time-consuming, and error-prone. Automated patent-specific proofreaders, like ClaimMaster and PatentOptimizer, have been around for a few years. However, the adoption of proofreaders like these seems to be accelerating. New AI-based proofreaders hitting the market, like BluePencil and PatentBots, are further evidence of how mainstream these tools are becoming.

6. Art unit prediction: Patent examination is still largely a human-driven process. And humans tend to be creatures of habit. As a result, the USPTO art unit to which an application is assigned once it’s filed can greatly affect a number of factors during prosecution, such as time to first action, number of actions before allowance, and, ultimately, the chances of ever being allowed.

In an effort to provide some control of the outcome, companies, like Juristat, provide an art unit prediction service. Coupling these insights with art unit analytics, such as that provided by BigPatentData, practitioners are able to adjust claim language to affect classification to improve prosecution outcomes and provide more realistic expectations to their clients.

7. Docketing: The patent process is a deadline-driven one. Missing deadlines can cost dearly in late fees and, for some deadlines, can cause the application to go abandoned. As such, docketing is one of the most critical aspects of any patent practice. Traditionally, the intake of USPTO correspondence and entry of corresponding deadlines is performed by a team of docketers. Beyond calendaring errors, the stress and monotony of these positions often result in moral issues and costly turnover.

Automation is becoming more and more prevalent in the patent docketing world. BlackhillsIP, for example, uses automation to augment its human docketers, while AltLegal provides a fully-automated solution. Both companies report cost savings and reduction in docketing errors. Building off of docketing, areas of opportunity for future PatentTech solutions include automated client reporting as well as schedule generation and workflow management for practitioners.

8. IDS preparation and management: Information disclosure statements (IDSs)–the mechanism by which patent applicants report known prior art to the Patent Office–make up another very tedious and error prone component of the patent procurement pipeline. Conventionally, this is often managed with spreadsheets, which is a problematic approach for obvious reasons. One of the earliest in the current PatentTech wave, SyncIDS, manages reference citations and relationships and generates ready-to-file USPTO-compliant IDS forms.

9. Prosecution: Preparing written responses to Patent Office rejections is one of the most time-intensive tasks for patent practitioners. With intense budget pressure, practitioners have found ways to maximize efficiency and leverage. Each office action response is unique, but there is definitely a rhythm to generating these documents. Traditionally, response “shells” are often produced by a paralegal or patent secretary. The shells include bibliographic info, claims in their current state of amendment, and an outline of the rejections in the office action. Shells take time and cannot have any errors. But due to the formulaic nature of these documents, shells are also great candidates for automation. Companies like ClaimMaster and TurboPatent offer automated shell generation as well as office action response proofreading.

When it comes to the practitioner’s part of preparing an office action response, examiner statistics are becoming essential. Examiner statistics are available from PatentBots, BigPatentData, and other sources. Practitioners can make data-driven decisions for things like “Should I appeal or file an RCE?” or “Have we successfully argued this particular issue in the past?”. One clear area of opportunity for the prosecution stage is automated claim charting, which could be leveraged during office action response drafting as well as infringement analysis, examination, and other aspects of patent law.

10. Strategic counseling/planning: One of the highest value-added parts of patent practice is strategic counseling to help solve business issues having an IP component. The analysis often considers various business objectives, likelihood of positive outcomes at the Patent Office, and the associated projected costs.

Patent filing strategies can be informed by a mapping between certain products (e.g., a competitor’s) and relevant patent claims (e.g., in an applicant’s portfolio and/or their competitor’s portfolio). Think of it as the opposite of a product clearance analysis where opportunities for patent protection are easier to identify. This is one of the myriad uses of ClearstoneIP’s platform, which also facilitates analyses like clearance/reverse clearance, FTO/reverse FTO, assessing licensing opportunities, enforcement analysis, competitor monitoring, etc.

Big data insights, like from BigPatentData, can help patent practice managers answer questions like “Should we prepare the client for lengthy prosecution?” or “Who at the firm is familiar with this technology?” or “Where is our prosecution practice most/least profitable?”. For in-house counsel, possible insights can inform decisions like “Should we pay for an examiner interview?” or “Which of our firms have handled this particular issue?” or “To which firms should we send more/less work?”.

More and more PatentTech companies are hitting the market and the rate is accelerating. Indeed, the companies mentioned above are just a few examples in the growing numbers of PatentTech. We are beyond a first-movers-only market with each area outlined above becoming increasingly competitive. Only a few years ago, it seemed like automation and big data insights were barely, if at all, on the radar of patent practice leadership. Now, in today’s hyper-competitive market, it’s dominating the conversation.


  1. See Jacob Goldstein, How The Electronic Spreadsheet Revolutionized Business, NPR (Feb. 27, 2015),; also see Lisa Cumming, After VisiCalc Revolutionized Accounting In The 70s, AI Is The Next Big Breakthrough, BLUE J LEGAL (June 22, 2018), available at
  2. See James A. De Lapp, et al., Impacts of CAD On Design Realization, 11 Engineering, Construction and Architectural Management, Issue No. 4 (2004), available at
  3. The AIPLA/AIPPI/FICPI AI Colloquium Primer, AIPLA/AIPPI/FICPI AI Colloquium 2019 (February 2019), available at

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