企業ガイド
Lexis+ AI vs Westlaw AI
Lexis+ AI from LexisNexis and Westlaw's AI features from Thomson Reuters, including AI-Assisted Research and CoCounsel, add generative AI to the two largest US legal research databases.
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概要
Both use retrieval-augmented generation to base answers on their own cases, statutes and editorial content, with linked citations. The comparison matters because independent testing has found both tools can be wrong, so choosing between them depends on how each grounds its answers and how well it performs on your own test questions.
ディープダイブ
Lexis+ AI from LexisNexis and the AI features in Thomson Reuters' Westlaw add generative AI to the two dominant US legal research databases. LexisNexis launched Lexis+ AI commercially in late 2023 and later added a personalized assistant called Protégé. Thomson Reuters introduced AI-Assisted Research in Westlaw Precision in late 2023. The same year it acquired Casetext and its CoCounsel assistant, which it then folded into its product line. Both rely on retrieval-augmented generation (RAG). Instead of answering from what a language model memorized, the system searches the vendor's own collection of cases, statutes, regulations and secondary sources. It passes the passages it finds to the model and asks it to write an answer that cites them. Each vendor also draws on its own editorial assets: Westlaw: its headnotes, the West Key Number System and KeyCite, plus practice content in Practical Law; and Lexis: its headnotes and Shepard's, plus practice content in Lexis Practical Guidance. Citations link back to the source documents, and citator signals help show whether an authority is still good law. Grounding reduces made-up answers but does not eliminate them. A 2024 study by Stanford researchers found that both Lexis+ AI and Westlaw's AI-Assisted Research gave incorrect or misgrounded answers on a meaningful share of test questions. Westlaw's tool erred more often in that test, and the vendors disputed parts of the method. The subtler failure is misgrounding: citing a real case for a point it does not support. The practical conclusion is to choose between them based on your own testing, not marketing. Build a set of questions from your practice area whose answers you already know. Include: jurisdiction-specific questions; recent changes in the law; questions built on a false premise; and issues where the controlling authority is obscure. Then compare accuracy, whether each tool finds the controlling authority, how easily you can check its citations, and how it handles uncertainty.
戦略的影響
ベンダー戦略
ベンダーのロードマップは、チームが次に構築できる機能に影響を与えます。
費用と予算
商業条件と導入オプションは、長期的なコストとリスクに影響します。
リスクと安全性
企業のインセンティブは、製品のデフォルト、安全姿勢、オープン性を形成します。
The Future of Lexis+ AI vs Westlaw AI
Both companies are moving toward multi-step, agent-style research that plans queries, reads many documents and drafts memos. They are also linking research more closely with document drafting and firms' internal knowledge. These features make checking more important, not less, because longer outputs contain more claims to verify. Independent benchmarks for legal research AI are still developing, so firms will keep relying on their own test sets. Pricing and bundling are likely to shape adoption as much as quality does. The market may also shift as smaller legal AI companies and general-purpose assistants add research features.
現実世界の実装
A litigation group runs the same 30 jurisdiction-specific research questions, with answers the lawyers already know, through both platforms and scores accuracy and whether each tool found the controlling authority.
A lawyer asks each tool a question built on a false premise, such as a statute that was repealed, to see whether it corrects the premise or answers as if it were true.
An associate uses a generated research memo only as a starting point. She opens every cited case, reads the relevant passage and checks its citator flag before relying on it.
A law firm librarian compares how easily each platform shows the sources behind an answer, which affects how long lawyers spend checking the output.
リスクとガードレール
実際の制作ワークフローでは、発売の発表が安定性を上回る可能性があります。
API の価格設定やポリシーの変更により、一夜にして想定が崩れる可能性があります。
単一ベンダーへの依存により、ロックインと移行のコストが増加します。
実装ロードマップ
独自のタスクとデータセットを使用してプロバイダーを評価します。
統合する前に、プライバシー、セキュリティ、法的条件を確認してください。
モデルやベンダー全体でフォールバック計画を維持します。
ロードマップの変更がチームを驚かせないように、リリース ノートを監視します。
探検を続けましょう
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よくある質問
What is Lexis+ AI vs Westlaw AI?
Lexis+ AI from LexisNexis and Westlaw's AI features from Thomson Reuters, including AI-Assisted Research and CoCounsel, add generative AI to the two largest US legal research databases. Both use retrieval-augmented generation to base answers on their own cases, statutes and editorial content, with linked citations. The comparison matters because independent testing has found both tools can be wrong, so choosing between them depends on how each grounds its answers and how well it performs on your own test questions.
Lexis+ AI と Westlaw の AI 研究機能は両方とも、答えを根拠付けるためにどのような技術を使用していますか?
どちらのシステムも、独自の判例、法令、二次資料を検索し、言語モデルに、見つかった内容を引用する回答を作成させます。
法律調査AIにおけるミスグラウンディングとは何ですか?
根拠の誤りは、主張をでっち上げるよりも微妙です。権威は本物ですが、それに付随する主張は間違っています。
2024 年のスタンフォード大学の調査では、Lexis+ AI と Westlaw の AI 支援研究について何が判明しましたか?
この調査では、両方の製品でエラーが見つかりましたが、そのテストでは Westlaw のツールでエラーが多かったです。ベンダーは手法の一部について異議を唱えた。
このガイドが Lexis ではなく Westlaw に関連付けている編集資産はどれですか?
KeyCite と Key Number System はトムソン・ロイターの資産です。 Shepard's、Lexis の頭注、および実践的なガイダンスは LexisNexis に属します。
ガイドでは、テスト セットに誤った前提の質問を含めることを推奨しているのはなぜですか?
優れた調査ツールは、それに基づいて答えを構築するのではなく、廃止された法令などの誤った前提に気づき、修正する必要があります。
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