The company also launched Workflows, a drag-and-drop tool for automating complex document reviews, and Everlaw for Word, a Word add-in that links Bates citations back to source documents.<\/p>\n
But when I spoke yesterday with Everlaw founder and CEO AJ Shankar<\/a>, he said the news generating the most excitement among customers at the Summit was the company\u2019s strategy of opening its platform to the general-purpose and legal AI tools its customers already use \u2014 Claude, ChatGPT, Copilot, Gemini, Harvey, Legora and others \u2014 through Model Context Protocol (MCP) connectors.<\/p>\n Shankar calls this strategy Everlaw Everywhere.<\/p>\n \u201cOmni is great,\u201d Shankar told me. \u201cI think it\u2019s going to be clearly the best agent tool in our field. But the very clear daylight between what we\u2019re doing and what other folks in our field are doing on Everlaw Everywhere is probably the bigger news.\u201d<\/p>\n Usage of Everlaw\u2019s MCP is more than doubling every month, Shankar said, and that is before factoring in the Harvey and Legora connectors, that launch later this month.<\/p>\n Everlaw charges nothing to use the MCP connectors, neither to its users nor to the AI companies that integrate with it.<\/p>\n Although I was not at the Summit this year, Shankar met with me via Zoom for both an advance briefing on Oct. 15 and a follow-up conversation and demo yesterday, following his keynote on Wednesday.<\/p>\n Omni now subsumes Deep Dive, the AI question-answering tool that Everlaw made generally available after last year\u2019s Summit<\/a>. According to the company\u2019s press release, customers have since added more than 300 million documents to Deep Dive and asked it nearly 100,000 questions.<\/p>\n \u201cThere\u2019s no separate Deep Dive interface anymore,\u201d Shankar said. \u201cYou ask Omni, and it chooses when to ask Deep Dive for you.\u201d Customers with Deep Dive-enrolled databases will automatically transition to Omni as it rolls out.<\/p>\n Omni also has two other parts: a new Omni Agent, and Case Memory, a module that builds up knowledge of a matter over time.<\/p>\n Whereas Deep Dive retrieves relevant documents and synthesizes an answer to a single question, Shankar said that many questions require more than retrieval. They require cutting the data several ways \u2014 with communications analysis, document clustering, the data visualizer or structured search \u2014 the way expert Everlaw users do.<\/p>\n \u201cOmni Agent is basically an expert at Everlaw, and it can use all of those tools on your behalf,\u201d Shankar said. \u201cInstead of you having to go jump from one to the other, you ask it a question.\u201d<\/p>\n While Deep Dive can pluck answers out of the haystack, \u201csometimes your answers need to be sliced and diced out of the haystack,\u201d he said.<\/p>\n In Everlaw\u2019s internal evaluations against a known data set, Shankar said, the Omni Agent found about twice as many relevant facts as Deep Dive alone. \u201cIt turns out that everything else we\u2019ve built over the last 10, 15 years is very useful,\u201d Shankar said.<\/p>\n Shankar yesterday demonstrated the Omni Agent for me on the Mallinckrodt opioid litigation data set, a public collection of more than one million documents.<\/p>\n He started by asking, \u201cWho are the main custodians?\u201d That is a question Deep Dive cannot answer, he noted, because it requires counting across every document rather than sampling the relevant ones. Omni instead chose Everlaw\u2019s entities tool and returned a table of the top custodians by document volume.<\/p>\n Next he asked Omni to find the documents in which one custodian, Karen Harper, communicated about suspicious orders, organized by subject and parties. For that, Omni drew on three tools \u2014 entities, search and Deep Dive \u2014 and produced a table of email threads, the people involved, and a summary of each, with numbered citations to the underlying documents.<\/p>\n His third prompt asked for a timeline of problems with Mallinckrodt\u2019s handling of suspicious orders from 2008 through 2011. Omni\u2019s visible \u201cthinking\u201d trace showed it first scoping a search to that date range and then sending off eight Deep Dive queries, each following leads from the last.<\/p>\n Finally, Shankar asked Omni to draft a deposition outline of Harper based on the findings so far. It produced objectives, key exhibits and questions, using only the evidence it had already gathered. It also added a caution that counsel should verify exhibit completeness, dates and privilege issues before use.<\/p>\n \u201cIn like 10 minutes, I\u2019ve gone from, \u2018Who are the custodians?\u2019 to, \u2018I\u2019m going to depose Karen Harper, what should I ask?’\u201d Shankar said.<\/p>\n Omni lets users expand its reasoning to see each tool it called and each Deep Dive query it ran. A sources panel lists every cited document. Omni conversations are visible to all users on the project with view permissions, although only the user who started a conversation can ask follow-up questions.<\/p>\n For now, Omni is able only to answer questions, but Shankar said it will soon be able to take actions within Everlaw as well, such as creating and managing search term reports, creating assignment groups, preparing a production, or doing work in Storybuilder.<\/p>\n Everlaw also plans to let users invoke the Omni Agent from within Claude, Harvey and other outside AI tools.<\/p>\n The third pillar of Omni, Case Memory, addresses what Shankar called an undervalued problem in litigation. Consider a contract reviewer who spends months on a matter and reads 10,000 documents. When that reviewer leaves, the codes and notes remain, but everything else the reviewer learned \u2014 the cast of characters, patterns of behavior, theories about why people did what they did \u2014 does not.<\/p>\n Case Memory is designed to capture all that. Users tell it what matters in terms of issues, people, events and concepts, or they simply upload the complaint. It then reads documents as review proceeds, pulls out relevant facts, and coalesces them over time.<\/p>\n It delivers that knowledge primarily through Storybuilder\u2019s fact management tools, where it can suggest new facts, supply additional evidence for existing facts, or flag evidence that contradicts them. Every fact traces back to its source documents.<\/p>\n According to the press release, Case Memory\u2019s facts will be available to Storybuilder and, eventually, to the Omni Agent.<\/p>\n Meanwhile, several Am Law 100 law firms are already using Omni through an early access program. Everlaw expects Omni to be generally available in early 2027 as a premium offering, with pricing to be announced.<\/p>\n The other major product launch, Workflows, is not an AI tool. Rather, it lets review managers map a complex review on a drag-and-drop canvas \u2014 routing documents by search criteria or properties, creating assignments, applying codes, sending subsets for QC sampling or translation, and moving documents into binders or Storybuilder.<\/p>\n Steps can be configured to be done by people or automated, and managers can insert gates that pause the process for human approval. Workflows can be templated and reused across matters, and managers can see at any point where documents are in the process and whether they are stuck.<\/p>\n Most practitioners already run playbooks like these, Shankar told me, but they track them in spreadsheets or other manual ways. Workflows codifies them, which he said matters even more as outside AI tools begin driving Everlaw.<\/p>\n Eventually, he said, users will be able to initiate the workflow from within a tool such as Claude or Harvey, and it will run in Everlaw exactly as the user has configured it. \u201cThen you don\u2019t have to worry about whether the AI decided to do something different that day.\u201d<\/p>\n Workflows will be available in November at no additional cost. Everlaw says additional AI review steps are planned for later releases.<\/p>\n Everlaw for Word, the Storybuilder Word add-in, automatically links Bates citations in a draft to the source documents in Everlaw. Future releases will bring Deep Dive into the add-in so users can search and add citations without leaving Word.<\/p>\n It is available now at no additional cost to organizations using Storybuilder, outside of GovCloud.<\/p>\n The company\u2019s Everlaw Everywhere strategy has been taking shape through a series of integration announcements this year. Everlaw\u2019s Claude connector<\/a> went live first, in May. In August, the company announced four more integrations<\/a> and began describing itself as \u201cthe evidence layer\u201d for legal AI.<\/p>\nAn Agentic Everlaw Expert<\/h3>\n
Getting A Demonstration<\/h3>\n
![\"\"](\"https:\/\/www.lawnext.com\/wp-content\/uploads\/2026\/10\/Omni-Thinking-and-Tool-Orchestration-1024x683.png\" "\\"\\"")
<\/a><\/p>\nCase Memory<\/h3>\n
Workflows and Everlaw for Word<\/h3>\n
![\"\"](\"https:\/\/www.lawnext.com\/wp-content\/uploads\/2026\/10\/Workflows-Partial-Taller-1024x815.png\" "\\"\\"")
<\/a><\/p>\nEverlaw Everywhere<\/h3>\n