Everlaw Introduces Omni AI Suite and Opens Platform to External AI Tools

Oct 30, 2026
Everlaw introduced Omni, an AI investigation suite that coordinates its document analysis tools, alongside free connectors for outside AI services.

Everlaw introduced Omni, an AI investigation suite for legal cases, at its annual summit, according to LawNext. Founder and CEO AJ Shankar said customers showed particular interest in Everlaw Everywhere, which connects the platform with services including Claude, ChatGPT, Copilot, Gemini, Harvey and Legora through Model Context Protocol connectors.

Omni combines the existing Deep Dive question answering system with Omni Agent and Case Memory. Omni Agent selects Everlaw tools for tasks such as document searches, communications analysis, timelines and deposition outlines. Case Memory extracts facts as document review proceeds, links them to source material and can add them to Everlaw's Storybuilder tools.

Shankar said usage of Everlaw's MCP connectors is more than doubling every month, and Everlaw does not charge customers or AI providers to use them. Customers have added more than 300 million documents to Deep Dive and asked it nearly 100,000 questions, the company said. The company also introduced Workflows, a visual tool for automating document reviews, and Everlaw for Word, an add in that links Bates citations to source documents.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Legal AI Weekly, AI Programming Weekly or Daily AI Brief.

Also, consider following us on social media:

Free newsletter

Legal AI Weekly

The source for the Legal AI software news, analysis, emerging applications: contract review, e-discovery, research.

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more
Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.