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The patent system will look meaningfully different in a decade. Recent breakthroughs in the reasoning capabilities of artificial intelligence models gesture at a world where computer systems are capable of processing patent text at unimaginable speed, scale, and consistency. As these models continue to improve, the possibility of automating large amounts of procedural human intellectual labor within the patent system becomes less fantastical. Anticipating this possibility, two years ago we set about building a computer system capable of parsing, searching, and reasoning across every type and category of patent. Our first implementation of this computer system is a high-end prior art search service that is superior in every possible way to all other prior art search products on the market. The goal of this flagship product is to establish a reputation for competence and craftsmanship. This brand will be instrumental to fulfilling two objectives: first, the procurement of government contracts for software that drastically increases the precision of patent examination in the public sector; and second, the distribution of a suite of revolutionary software products to the private sector. Widespread adoption of our products will drastically increase the efficiency of labor at every point in a patent's lifecycle—harvesting, examination, prosecution, monitoring, pruning, litigation, licensing, and budgeting. The result will be: (a) the elimination a substantial share of patent practitioners from the workforce while substantially increasing the output and decisionmaking capacity of those who remain; (b) more certainty in the patent system as both error rate and patent pendency (i.e. the time required to examine a patent) inside the USPTO approach zero; (c) a continual reduction in the cost of patent work leading to less spending on intellectual property departments thereby allowing more spending on research and development; (d) an end to barbaric practices like thicketing, trolling, and counting which create oligopoly and decrease fairness in certain industries; and (e) increased dealmaking activity and patent value via decreased transaction costs. While the incumbents of this industry are fragmented between many outdated service and software vendors, our thesis is that there exists in this moment a unique and fleeting opportunity to build a new operating system for the patent system used by every corporate intellectual property department in the world. It may seem far-fetched to imagine the unification of the patent system under one single business. However, we may consider the following: (a) for the end user, considerable synergies are afforded by the agglomeration of various patent services under one interoperable framework; (b) the technology required to automate one function of the patent system is transferable to the automation of others, resulting in cost savings; and (c) there is a first-mover advantage both in the public sector where presumably only one player can receive the big government contract and in the private sector where no decisionmaker could justify deploying the second-best software to run their intellectual property department. In our journey there, the recurring obstacle to adoption we face will be skepticism. Beyond the years required to build products meeting our exacting standards, it will take many more years to convince our clients to trust our products. This is only prudent. The global economy would cease to function without the patent system. The patent system therefore requires a steward, not a profiteer. In Silicon Valley, there is sometimes a preoccupation with moving fast. Even so, this industry will be conquered by a business unafraid to be patient — patient in disbelief, patient in failure personal and professional, patient most of all in understanding that we are still not ready to hold so much power nor responsibility. We are still too reckless. We have too much ego. We do not know who we are yet. Hopefully we never fully do.

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GLENN YU is our President. He lives in Manhattan, NY. He holds an A.B. in English and Economics from Brown University.
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JOSHUA BECK is our Chief Executive Officer. He lives in Los Angeles, CA with his wife and four rescued cats: Binx, Dumbo, Fawn, and George. He holds a Sc.B. in Computer Science and Economics from Brown University. In a previous life, he worked at Susquehanna International Group pricing volatility options.
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KENNETH NOBLE was our third cofounder. He has since left to attend NYU School of Law but remains a trusted advisor. He holds an A.B. in English and Africana Studies from Brown University. Last summer he began work at Quinn Emanuel Urquhart & Sullivan as a summer associate.
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MIA TEIXEIRA is a computational linguist and was our first employee after we pivoted the business. She lives in Somerville, MA. She holds a B.S. in Physics from MIT and M.A. in Linguistics from UCLA.
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NORA MORIKAWA is a computational linguist. She lives in San Francisco, CA. She holds a B.A. in French and Anthropology from Hamilton College, an M.A. in Applied Linguistics from Boston University, and a Ph.D. in Linguistics from CUNY. Nora has two wonderful children, Astrid and Violet, who join us on calls from time to time.
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DEBORAH WONG is a computational linguist. She lives in Los Angeles, CA. She holds a B.A. in Linguistics from UCL, an M.A. in Linguistics from Cambridge University, and a Ph.D. in Linguistics from UCLA. Deb has a refined palate between her interests in tea, wine, cocktails, and food. When we go on retreat, Deb always picks where we eat.
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KYLE COX is a machine learning engineer. He lives in Austin, TX. He holds a B.S. in Mathematics from UT Austin. In his free time he likes to tweak his NBA forecasting model.
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IAN FANSELOW is a software engineer. He lives in Brooklyn, NY. He holds a B.S. in Computer Science from NYU. In 2024, Ian published his first book “Worlds Apart”. We all read it for our company book club. It’s the first book in a series about two teenagers who have been abducted by aliens. The protagonist, Lora, is a lesbian. She must fight aliens to save her lover, Evelyn. It remains to be seen whether Lora’s feelings will be reciprocated.
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ITALO NABUCO is a software developer. He lives in Teresina, Brazil. He holds a B.S. in Computer Science from the Federal Institute of Education Science and Technology of Maranhao in Brazil. Italo loves K-pop.
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QINGCHEN WANG is a machine learning scientist. He lies in Tallahassee, FL. He holds a B.A. in Computer Science and Biology from the University of British Columbia, an M.A. in Machine Learning from UCL, and a Ph.D. in Machine Learning from University of Amsterdam. He is a Kaggle grandmaster. This is the highest rank that a user can achieve on Kaggle, a popular platform for data science and machine learning competitions.
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MEGAN LEVIN is a software engineer. She lives in co-op she started with several of her friends called “Horse House” in Somerville, MA. She holds a B.S. in Computer Science from MIT.
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BLAKE WILKEY is a machine learning scientist. He lives in Chattanooga, TN. He holds an A.B. in Mathematics from Harvard University. Blake is a lifelong pianist and composer, with notable works performed by internationally renowned musicians like Tae Kim.
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VICTOR WANG is our Director of Patents. He lives in Great Neck, NY. He holds a B.S. in Electrical Engineering from Columbia University and JD from Cardozo School of Law. As a former patent examiner, prosecutor, litigator, and professor, Victor has dedicated his life to patents.
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MATTHEW CZUBA is a computational linguist. He lives in Jersey City, NJ. He holds a B.A. in Linguistics and Mandarin from Marlboro College, an M.A. in Theoretical Linguistics from Tsing Hua University, and an M.A. in Linguistics from UCLA. Separately, Matt also spent three years in Taiwan researching Chinese syntactic and semantic theory. Matt is a practitioner of neigong (内功). In Chinese, neigong means "internal power” and teaches the cultivation and refinement of internal energy (qi) through breathing exercises and movement.
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JEFF BOOMER is our Director of Partnerships. He lives in Providence, RI. He holds a B.A. in History and a B.S. in Mechanical Engineering from the University of Virginia. Jeff spent 12 years at the Patent Office where he held the roles of Patent Examiner, Classification Specialist, and Review Quality Assurance Specialist. On most weekends, Jeff can be found in his studio where he paints and exhibits color field paintings that depict algorithmic patent figures.

1. Prior art search. The most precise prior art search in the world, capable of searching across every category of technology, comprising: (a) a syntactic parser that represents the components and limitations of a patent claim as a hypergraph, (b) a claim constructor that enriches the components of the hypergraph with precise definitions of the claim language in view of the specification, (c) a semantic search engine specifically designed to source relevant prior art references based on the enriched claim language, (d) a re-ranking algorithm that uses large language models to tag each reference with the existence or nonexistence of the hypergraph elements, and (e) a mapping system that traverses the hypergraph to identify and justify equivalencies between the claimed language and disclosures in the prior art.

2. Office action response analysis. A tool that highlights potential avenues for dispute with the Office and generates a set of potential claim revisions; comprising: (a) a syntactic parser that represents the components and limitations of a patent claim as a hypergraph, (b) a claim constructor that enriches the components of the hypergraph with precise definitions of the claim language in view of the specification, (c) a matching system that aligns the examiner's rejection with corresponding hypergraph components, (d) a reasoning system that considers each component in the hypergraph in view of both the prior art and logic of the examiner's rejection in order to precisely pinpoint which limitations or sub-limitations of the claim lack full disclosure, and (e) a claim amendment generator that drafts narrowing amendments supported by the specification that add additional layers of novelty and non-obviousness in view of the prior art in the prosecution history.

Julius Sun has been our friend since the third grade. At our high school graduation, Julius was our salutatorian, Josh was our valedictorian, and Glenn was our class president. When the three of us matriculated to Brown University together, we were roommates.

Joseph Abraham Zurier was our first investor. Joe and Glenn met more than a decade ago all because of the assigned seating at an Academic Decathlon. The day they met, Joseph Abraham became the first person in Rhode Island history to receive a perfect score in the mathematics category. Upon graduating from MIT, Joe spent a few years at Jane Street before leaving for greener pastures.

Tejas Narechania met with us for about two years to teach us patent law when we first became interested in this space. Once upon a time, Tejas clerked for Justice Breyer of the Supreme Court. He is a Professor of Law at UC Berkeley.