Everlaw expanded Deep Dive to open beta, enabling legal teams to query entire document corpuses in seconds using natural language. The tool synthesizes answers grounded in facts extracted from specific documents and provides citations and links to underlying sources for verification. Deep Dive identifies roughly 10,000 potentially relevant documents, narrows them to about 50 most pertinent sources, extracts and scores specific facts, then synthesizes responses with full citations. In a 1.3 million-document Mallinckrodt opioid litigation dataset, the tool returned scientifically grounded explanations with citations to specific corpus documents. Everlaw also secured FedRAMP certification for its AI Assistant features, supporting use in regulated government environments.
Deep Dive, which the company had previously code-named "Project Query," allows legal teams to query entire document corpuses in seconds using natural language questions. The tool synthesizes answers grounded in facts extracted from specific documents, providing citations and access to underlying source materials for verification. "Deep Drive helps legal teams uncover insights in an entire corpus of data sooner by simply asking questions related to specific issues, parties, or events and get answers in just seconds," the announcement said.
During a media briefing at ILTACON, Everlaw CEO AJ Shankar demonstrated the technology using the 1.3 million document dataset from the Mallinckrodt opioid litigation. He showed how the AI tool processes queries by first identifying relevant document subsets, extracting pertinent facts, scoring their relevance, and then synthesizing responses with full citations. When Shankar asked Deep Dive how opioids work, for example, it returned what appeared to be a scientifically grounded explanation, drawn from documents within the corpus, complete with citations to the specific documents containing the information.
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