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    Legora’s task-by-task approach to choosing legal AI models

    Legora says different models lead on different tasks and the frontier changes almost weekly. It argues lawyers should focus on whether the work holds up, not which model did it.

    SoleioSO
    logan bartlettLB
    LegoraLE
    4 Sources, ,

    TLDR

    Legora says it uses the best available model for each legal task and invests in a system where intelligence compounds and remains editable, auditable and portable. The company says it further trains models when it knows doing so delivers better performance for customers on a specialized task. “Training is a tool, not a strategy,” it writes.

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    4 Sources, first seen 20d ago

    Combined views

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    4 Sources, first seen 20d ago

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    4 Sources

    Legora@WeAreLegoraWho owns the model? Where should a legal team's intelligence live? These questions are at the center of many conversations in legal AI, but we think the most important question to answer is: what produces the best outcome for every legal task? As CTO @jacsebl and CPO Bryan Tsao explain, there is no best model. Different models lead on different tasks, and the frontier changes almost weekly. At Legora, we use the best available model for each task, and invest in the system, where intelligence compounds and remains editable, auditable, and portable. We post-train when we know it delivers our customers better performance on a specialized task. Training is a tool, not a strategy. No lawyer should have to worry about which model did the work. Just whether the work holds up.20d
    logan bartlett@loganbartlettRT @WeAreLegora: Who owns the model? Where should a legal team's intelligence live? These questions are at the center of many conversation…20d
    Max Junestrand@MaxJunestrandThere is no best model. There's a lot of noise about models right now. Who is training them, who owns them, where legal intelligence should live. One question actually matters: what produces the best outcome for the legal task in front of you? That's how we decide things at @WeareLegora. We optimize for the end-to-end outcome on a legal task. The model is one layer of that system, not the system. Models are uneven and the frontier changes almost weekly. One model plans a long job well, another runs deep analysis across thousands of documents. Some have to be told exactly what to do, and some are fine with a vague brief. They all break in different ways. So our lawyers write evals and we test them with the Legora BAR, our benchmark for agentic reasoning. Every model takes every test, and the model that wins gets the work. We post-train when we know it buys our customers better performance on a specialized task. Training is a tool we reach for when it helps, nothing more than that. The intelligence that compounds sits in the orchestration layer. Precedents, review standards, client requirements. That knowledge has to stay editable, auditable and portable. In our system, a changed review standard is an edit that takes effect the same day, with no new model training required. No lawyer should have to worry about which model did the work, any more than they think about which chip is in their laptop. They should only care about the quality of the work. That's what we are focused on. If you want the engineering version of this argument rather than the CEO version, our CPO, Bryan Tsao, and CTO, @jacsebl, take it apart in the video below.20d
    Soleio@soleioRT @MaxJunestrand: There is no best model. There's a lot of noise about models right now. Who is training them, who owns them, where legal…20d

    4 Sources

    Legora@WeAreLegoraWho owns the model? Where should a legal team's intelligence live? These questions are at the center of many conversations in legal AI, but we think the most important question to answer is: what produces the best outcome for every legal task? As CTO @jacsebl and CPO Bryan Tsao explain, there is no best model. Different models lead on different tasks, and the frontier changes almost weekly. At Legora, we use the best available model for each task, and invest in the system, where intelligence compounds and remains editable, auditable, and portable. We post-train when we know it delivers our customers better performance on a specialized task. Training is a tool, not a strategy. No lawyer should have to worry about which model did the work. Just whether the work holds up.20d
    logan bartlett@loganbartlettRT @WeAreLegora: Who owns the model? Where should a legal team's intelligence live? These questions are at the center of many conversation…20d
    Max Junestrand@MaxJunestrandThere is no best model. There's a lot of noise about models right now. Who is training them, who owns them, where legal intelligence should live. One question actually matters: what produces the best outcome for the legal task in front of you? That's how we decide things at @WeareLegora. We optimize for the end-to-end outcome on a legal task. The model is one layer of that system, not the system. Models are uneven and the frontier changes almost weekly. One model plans a long job well, another runs deep analysis across thousands of documents. Some have to be told exactly what to do, and some are fine with a vague brief. They all break in different ways. So our lawyers write evals and we test them with the Legora BAR, our benchmark for agentic reasoning. Every model takes every test, and the model that wins gets the work. We post-train when we know it buys our customers better performance on a specialized task. Training is a tool we reach for when it helps, nothing more than that. The intelligence that compounds sits in the orchestration layer. Precedents, review standards, client requirements. That knowledge has to stay editable, auditable and portable. In our system, a changed review standard is an edit that takes effect the same day, with no new model training required. No lawyer should have to worry about which model did the work, any more than they think about which chip is in their laptop. They should only care about the quality of the work. That's what we are focused on. If you want the engineering version of this argument rather than the CEO version, our CPO, Bryan Tsao, and CTO, @jacsebl, take it apart in the video below.20d
    Soleio@soleioRT @MaxJunestrand: There is no best model. There's a lot of noise about models right now. Who is training them, who owns them, where legal…20d