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The interview covers how Legora builds and evaluates an AI legal agent when client data is off-limits to the company. Its main lesson is that evaluation has to work without direct access to traces, so the team relies on other signals to measure quality. The reported jump in citation accuracy from 70% to 99% after a single model release, with no changes on Legora's side, also shows how much product performance can shift with upstream model updates.
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Sursă care acoperăLatent Space
Ce este aceastaLectura unui model asupra articolului și a acoperirii conexe, scrisă pentru aiqbench. Nu sunt cuvintele publicației.
Building Legal Agents When You Can't See the Data - Jacob Lauritzen, CTO of Legora
Latent Space2 min de cititArticolul și perspectiva sunt în engleză.
Legora can’t read a single trace of what its agent does for a lawyer. The data belongs to the law firm’s clients. How do you build and test an agent when you can’t see its work? Jacob Lauritzen is the CTO of Legora, one of the fastest-growing companies...
Legora can’t read a single trace of what its agent does for a lawyer. The data belongs to the law firm’s clients. How do you build and test an agent when…
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