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Global content and technology provider Thomson Reuters has launched Thomson, its first proprietary large language model, developed in-house, which it says was trained and is run at a fraction of the cost of comparable frontier models.
The launch of Thomson, Thomson Reuters said in a statement, “marks a new chapter” for the global provider: “The company has always owned the content, the expertise, and the tools professionals rely on every day. Now it owns the model too.”
The provider noted that Thomson has been built on decades of proprietary content, technology, and domain expertise, and the end result is “a model built to Fiduciary-Grade ™ standards, at a fraction of the typical cost”.
Thomson Reuters chief technology officer Joel Hron said: “For years, the AI industry has treated scale as the answer: bigger models, more computers, more money. Thomson shows there is another path.”
“Start with a strong foundation, specialise deeply for the work that matters, and you can build intelligence that is highly capable, far more efficient and entirely under your control. We think that changes the economics of professional AI.”
Thomson has an open-source foundation, state-of-the-art mid-training and post-training techniques, drawing on decades of authoritative content from Westlaw, Practical Law, Checkpoint, and Reuters, with hundreds of subject matter experts integrated from the design of training objectives through to the final evaluations, the provider continued, adding that the model has been trained on less than 10 per cent of Thomson Reuters content so far.
Thomson Reuters chief executive Steve Hasker said: “Thomson proves what’s possible when you build AI on decades of proprietary content and editorial expertise.”
“That’s an advantage only Thomson Reuters has, and it shows in the results: our early evaluations put Thomson on par with the latest frontier models across a range of tasks. We’re putting it to work in CoCounsel Legal, with more capabilities and sovereign AI options to come. This is the bar we intend to keep raising.”
The provider also noted that legal professionals are paying closer attention to questions of AI sovereignty: how a model is trained, what behaviours and biases live inside it, where it runs, and how the privacy of their information is protected. Thomson, it said, marks a shift into a world where those questions are answered directly, not left to third parties alone.
“Thomson shows a meaningful uplift from its base model in instruction following, the ability to execute complex, multi-part professional instructions precisely. It demonstrates an even greater uplift in navigating dense, domain-specific content, the kind of nuanced reasoning the hardest professional tasks require. It is also able to be trained alongside Thomson Reuters proprietary tools like Westlaw and Practical Law, which makes it more sophisticated and nuanced in its work,” the provider said.
Thomson’s first deployment is inside Tabular Analysis in CoCounsel Legal, and it will be available in Tabular Analysis for law firms and corporate legal departments in the upcoming release.
