This is like giving every lawyer a super-fast, tireless research assistant that has already read millions of cases and documents, and can instantly pull out the most relevant ones, summarize them, and suggest arguments.
Traditional legal research is slow, manual, and expensive. Lawyers spend many hours searching through cases, statutes, and secondary sources, risking missed authorities, inconsistent quality, and write‑offs on non‑billable time.
Tight integration with proprietary legal content, citators, and editorial enhancements; workflows embedded in existing research platforms; accumulated user behavior data improving ranking and recommendations over time.
Hybrid
Vector Search
Medium (Integration logic)
Context window cost and latency for running LLM-augmented research over very large proprietary corpora.
Early Majority
Focus on deeply integrating AI into legal research workflows (search, summarization, recommendations, and drafting support) on top of large, curated legal databases, rather than offering a generic horizontal AI assistant.