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Syntheia 通过新颖的方法降低代币成本
Horace Wu 的 Syntheia 发现，在应用人工智能之前，通过采用不同的方法来“分割”合约，简单地说，...
来源:Artificial LawyerHorace Wu’s Syntheia has found that by taking a different approach to how a contract is ‘sliced up’ before applying AI,to put it simply,lawyers can significantly reduce their token costs. （请参阅下面的 AL 采访。）
The token savings are therefore not gained by switching models or ‘rerouting’ to cheaper LLMs, but by changing the starting conditions of the doc review.
The findings come as the debate about how to reduce rising token costs in legal tech widens across the market.
The company stated that: ‘In transactional legal work, the cost of an LLM reading a document is typically far larger than the cost of it reasoning over the answer.
‘In our tests, the length of the final answer barely varied between methods, while the amount of text fed into an LLM varied by up to 30×.
‘这个差距是我们可以节省大量资金的地方。 As AI agents increasingly decide for themselves what to retrieve and read, that matters even more.
‘Syntheia’s research team tested two structured retrieval methodologies for transactional legal text, both built on our structure-aware document indexing technology, against full document injection on a 20-question benchmark spanning real credit facility agreements, limited partnership agreements, and share purchase agreements.
And here are the headline results:
以及，
In short, by focusing on what is likely to be most relevant you can massively cut down on token use.
AL Interview with Horace Wu, founder of Syntheia.
您使用什么模型来实现这一目标？
这项研究是两个月前开始的，所以是 Claude 4.6 作为 Q&A 的主要引擎。
告诉我们有关用例的信息。
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