Automating the Practice of Law

With transparency and efficiency


Automatically Evaluate Your Entire Patent Portfolio

our ask-alice product will find your weakest patents

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Give Your Legal Assistant Their Own Assistant

automate your workflow to accomplish the same tasks in a quarter of the time

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We are attorneys and technologists

Formed in 2017, Lawtomata was born from our own desire to automate the drudgery of patent law, and simultaneously achieve superior results with artificial intelligence. By intelligently applying machine learning and automation to legal problems, we can help you slash your costs, while realizing the same or better quality.


You may have noticed that machine learning and artificial intelligence are showing up more frequently in today’s headlines, and the fruits of these technologies are insinuating themselves into every part of our lives. We get movie recommendations from Netflix, speak conversationally to Amazon’s Alexa, and watch Google’s AlphaGo program beat one of the best Go players in the world. Yet, this explosion in AI has been largely invisible to most people. As Elon Musk put it, “The pace of progress in artificial intelligence … is incredibly fast. Unless you have direct exposure to groups like Deepmind, you have no idea how fast—it is growing at a pace close to exponential.”

The vast improvements we have seen in machine learning over the past decade have largely been driven by the incredible gains made by neural networks, programs designed to mimic the mechanisms of the human brain. The success of neural networks has been driven in turn by two primary factors: (1) dramatic improvements in computing power, and (2) the dawn of the age of “Big Data.” With better algorithms, faster processing and terabytes of information, the sky is truly the limit.

Our company’s mission is to bring cutting edge machine learning and artificial intelligence to bear on the practice of law. As the Patent Office digitizes its workflow, more and more data is available to support learning algorithms. From this data, we can glean interesting and pragmatic insights into the value of our existing patent portfolios and how to improve our patent drafting process from the outset. We can also leverage powerful optical character recognition algorithms and natural language processing to automate and improve paper-based workflows, and give you more time to tackle legal issues.

Build a better patent portfolio