Legora如何在不接触客户数据时评估法律智能体
Latent Space采访了Legora首席技术官Jacob Lauritzen，介绍公司在客户上传内容和工作轨迹均受保密约束时构建法律智能体的方法。Legora评估团队通过模拟客户业务重建法律工作流，包括一个包含10,000份文件的数据室；据报道，其智能体可处理文档起草、合同审查、尽职调查和多智能体协作。Latent Space还报道称，Legora的ARR已超过1亿美元，客户超过1,800家。
Legora借助模拟评估测试智能体，为无法查看生产轨迹的团队提供了可参考的方法，但相关能力和性能数据仍需独立验证。
In this episode, we chat with Jacob Lauritzen, CTO of Legora, following the announcement of their $550M Series E at an $8.8B valuation a couple weeks ago. We talk about what it takes to build AI agents for lawyers and what other people building agents can learn from that work.
Legora started in a Stockholm basement with a simple product: ChatGPT, Swedish law, and a search tool. Jacob had already been through YC with his own startup when he helped Max Junestrand with the application for Leya (now Legora). He later joined as head of engineering and is now CTO.
Today the agent drafts and edits Word documents, reviews thousands of contracts at once, and coordinates work between lawyers, their clients, and other agents. The company passed $100 million in ARR in April, less than 18 months after launch, and now has more than 1,800 customers. It raised $550 million in March at a $5.55 billion valuation, then another $550 million in October at an $8.8 billion valuation. Its latest acquisition, Wexler, was its fifth just this year.
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