法律 AI // 资讯总览
需要被持续追踪的
法律 AI 信号。
本期索引按监管、判例、实务与研究归档;可依主题或关键字定位已发布记录。
法律 AI // 资讯总览
本期索引按监管、判例、实务与研究归档;可依主题或关键字定位已发布记录。
原题: Draftwise Launches ‘Legal Ontology’ to Capture The Judgment Layer
Draftwise推出名为"Legal Ontology"的新产品,旨在利用律所内部文档数据之间的关联,提取其中蕴含的法律知识与律师判断。该技术通过分析文档间的关系,将分散的文件转化为结构化洞察,帮助律师更高效地检索和应用既往经验。
展示来源全文,完整内容以原文页面为准。
Draftwise Launches ‘Legal Ontology’ to Capture The Judgment Layer
24th August 2026
artificiallawyer
AI + KM
Comments Off on Draftwise Launches ‘Legal Ontology’ to Capture The Judgment Layer
Draftwise has launched ‘Legal Ontology’, which leverages knowledge and lawyer judgment embedded in the relationships between data sitting inside a law firm’s documents. The move was inspired by client demand – especially following the recent Kirkland move, they said. See AL Interview with CEO, James Ding, below.
The contract-focused company explained that law firms can use this ‘connected view’ for just about everything that has gone on in past deals, including ‘negotiated positions, rights, and obligations across their entire practice’.
It will also show how the firm’s work for different clients differs, and also how ‘a change in one place [in a contract] could affect relationships and obligations elsewhere’.
In short, there is value here because Ontology can ‘surface insights that would otherwise require lawyers to piece together information across years of agreements, side letters, amendments, and other records’.
The company gave the example of how in a funds team, lawyers could ‘identify which LPs hold a particular right, trace how it was negotiated and amended, compare that position with the firm’s experience across other LPs, and determine whether extending it to another LP could create obligations elsewhere’.
In short, it’s showing you a crystallisation of the firm’s judgment calls on how it formed certain matters, and also reveals – in a connected way – how clients reacted during the negotiation of a matter.
Is this a big deal?
It connects to a growing surge of interest from law firms to capture more than access to relevant past files, and instead to focus on judgment – i.e. the decisions of the firm’s lawyers that reveal their combined experience and choices.
In short, this is KM going up a level, or rather digging down deeper into the meaning hidden within and between key elements of documents. And through this: greater meaning and insight.
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Legal Innovators New York – Nov 17 and 18 – the landmark legal innovation conference: Day One: law firms, Day Two: inhouse.
—
And now the interview with James Ding, CEO, Draftwise.
Why do this now?
Client interest. Inspired by the Kirkland announcement, our existing customers approached us with this request. I was one of the software architects behind Palantir’s platform, and the Draftwise team has the highest concentration of ex-Palantir expertise in legal. I myself hold multiple patents for the technical work.
You say ‘Ontology captures the relationships between the things those documents describe’ – how does this work?
Ontology models all the moving pieces of a domain, including elements ‘smaller’ than a document. For example, a contract or a redline is actually the culmination of hundreds of decisions, so a document does not reflect actual decision making. In contrast, Ontology is a relational system that models decisions at a granularity that document-based modelling can’t achieve.
How far does this focus on the individual lawyer vs the firm as a whole? How do the two mesh together?
Both. Individual lawyers make hundreds of decisions on a daily basis, e.g. how deep should diligence go, should I grant these rights to the LPs in their side letter, etc, and the Ontology framework is the means by which an organization can raise the floor for their operations by optimizing on the individual level. This is a critical tenet to the Ontology framework, about how elevating individuals helps the firm win.
There seems to be a big focus now customization and preferences, and that connects to context and data capture – how do you see these elements combining?
I would go further and say that customization and preferences are a poor substitute for what organizations really want, which is to own and amplify their differentiated expertise. Customized preferences are a symptom of the limitations of off-the-shelf tools, which as you’ve seen Kirkland quite publicly declare, are inadequate for organizations who want to retain their competitive advantage in the era of AI. You have to reject the premise and instead embrace the alternative, which is that organizations should own their own alpha.
Thanks James!
Two Major Legal Innovators Conferences this November
Come and join us in New York and London this November at Legal Innovators!
Legal Innovators UK – London, Nov 4 and 5
And, then Legal Innovators New York – Nov 17 and 18.
After another fantastic Legal Innovators California, where we had speakers from OpenAI, Y Combinator, Google, Meta, and many more pioneering organisations; and our stellar inaugural event in Paris this June, we are now looking forward to the landmark conferences in London and New York, both in November, and both across two days: Law Firm Day, and Inhouse Day.
Legal Innovators UK – London, Nov 4 and 5
Legal Innovators New York – Nov 17 and 18
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从律所内部文档中提炼律师判断,本质上是对承载客户机密、律师工作成果及执业经验的原始数据进行深度再利用,核心风险在于如何在不泄露客户秘密、不违反执业保密义务及不加剧偏见的前提下实现知识增值。
文书与研报规范引注
《Draftwise发布法律本体产品提取律所文档中的律师判断》(来源: Artificial Lawyer,发布日期: 2026/08/30,访问链接: https://www.artificiallawyer.com/2026/08/24/draftwise-launches-legal-ontology-to-capture-the-judgment-layer/)