Legora reviewed 41 documents in minutes with GPT-6 Astra
热度趋势
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官方发布带来OpenAI 模型更新信号，适合跟踪能力变化、生态影响和后续落地。
Legora 是一个面向法律和专业工作的代理操作系统，被超过 100,000 名专业人士使用。Legora 使用其代理推理基准 (BAR) 对 GPT-6 Astra 进行了评估。结果显示，在财务报表工作流程中，GPT-6 Astra 的性能比之前的模型提高了近 40%。在 BAR 中的所有任务中，平均性能提升约为 3%。这使得初次审查更快，记录更清晰，最终决策仍由法律专家做出。
Legora is an agentic operating system for legal and professional work, used by more than 100,000 professionals across more than 1,800 in-house legal departments and law firms in over 50 markets. Its legal engineers work directly with customers to understand how they operate and adapt Legora to their end-to-end workflows, from contract and agreement review to legal research.
One of the more tedious workflows is financial-statement tie-out: checking every figure in draft accounts against trial balances, a consolidation schedule, and the previous year’s accounts until each item agrees. As Legora Legal Engineer Percevale Perks says, the work “can take an entire evening, sometimes days.”
Processing complex financial context at scale
Using GPT‑6 Astra, Legora’s Agent completed the tie-out across 41 documents in a single run. Legora says the Agent did the work within minutes: checking every balance against its supporting schedule, surfacing breaks in the amounts, and recording each check. The result gives the legal professional a granular record of every line item and figure to review.
“I think what changed before and after is the processing power, the ability to ingest such a large number of documents, digest really complex information, and get all of those different line items and figures.”
—Percevale Perks, Legal Engineer, Legora
The Agent handles the exhaustive comparison, while the expert remains responsible for the judgment call on each result. That approach of keeping a human in the loop is central to how Legora is extending its platform beyond legal work into audit, tax, compliance, and risk.
Improving accuracy, completeness, and reliability
Legora evaluated GPT‑6 Astra with the Legora Benchmark for Agentic Reasoning (BAR), which measures performance on end-to-end legal tasks drawn from real-world use cases. Legora reports that GPT‑6 Astra improved performance by nearly 40% over the previous model on this financial-statement workflow. Across all tasks in the BAR, the improvement averaged about 3%.
In the tie-out, Legora saw gains across what Percevale describes as accuracy, completeness, and reliability. GPT‑6 Astra found all four errors Legora had planted in the accounts, including a £500,000 gap hidden in the revenue note. It checked every balance against its supporting schedule and recorded each check. And it retained every check the previous model got right as well as completed around 50 more.
The result is a more complete and faster first pass and a clearer record to review, while the final decision stays with the legal expert.