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What to expect from Casetext?

The Californian startup Casetext is currently making waves. Thomson Reuters is set to spend an astronomical sum of $650 million to acquire a controlling stake in the company. Casetext’s standout product is “CoCounsel,” an artificial intelligence legal assistant that uses ChatGPT-4 from OpenAI.


Of course, this is not entirely surprising, as there is already a race among lawtech companies to incorporate generative artificial intelligence into their platforms, especially in their enterprise resource planning (ERP) systems. However, this acquisition goes beyond mere strategy, as offering generative AI solutions is an inevitable path. In reality, Thomson Reuters will be able to offer all its other services to more than ten thousand law firms and Legal Departments, which is currently the number of Casetext’s clients.


Clearly, like in any classic merger and acquisition operation, Thomson Reuters’ interest in Casetext has been longstanding and preceded by a thorough evaluation of the benefits, especially in terms of competitiveness, offered by “CoCounsel.” In a market with acute symmetry, “CoCounsel” captured attention due to its impressive valuation, not only because of its extensive referred database but also, and more importantly, for coming closer to automating certain tasks, such as document review, legal research, deposition preparation, and contract analysis in a short amount of time.


This execution capability, coupled with the known strength of ChatGPT-4 in efficiently processing large volumes of legal data, positions Casetext and, of course, “CoCounsel” at the forefront of the intersection between law and technology. Could this finally lead to scalable legal services that are less dependent on human capital?


The subject is not entirely new. A few years ago, lawtech Atrium promised to revolutionize legal services. In its pitch, it raised over seventy million dollars in funding but later announced a strategic restructuring, a euphemism for stopping the burning of investors’ money. Justin Kan, its founder, is a well-known figure in the technology market; he was one of the creators of “Justin.Tv,” a site that unlawfully streamed sports broadcasts and caused significant trouble for broadcasters. In other words, a transgressor by nature. However, some mistakes made by Kan can be listed:

  1. Not being a lawyer, he underestimated the legal market, treating it like any other market where an opportunity could be seized (unlike Casetext).
  2. The shortcomings of the legal market still depend on and will be overcome through human capital (or not, if relying on Casetext and “CoCounsel”/ChatGPT-4).
  3. Envisioning exponential growth in an industry that seeks customization. Templates alone are not enough (can “CoCounsel” overcome this previously insurmountable obstacle?).
  4. An abundance of platforms with the same model as Atrium. High competition with relatively uniform demand (can Casetext truly stand out in such a competitive landscape?).
  5. Slowness in recognizing that more and more platforms will migrate to the “one-stop mart” model (potential seen by Thomson Reuters).
  6. And of course, an overestimated and disproportionate valuation (Is Casetext, a startup, really worth so much?).

Past examples guide future behavior. The mistakes made by Kan, a seasoned and successful serial entrepreneur, certainly served as a reference for the founders of Casetext. We will see how “CoCounsel” behaves and whether it can truly achieve the biggest challenge in the legal market: automating tasks that inherently require human capital. But here’s a tip: understanding the legal market is not for amateurs.


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