Mentioned in 9 AI use cases across 2 industries
This is about using AI as a super-fast paralegal that can read millions of emails and documents, find what matters for a case, and summarize it for lawyers, instead of humans doing that work manually.
This is like giving eDiscovery and litigation support teams a super-smart research assistant that can read huge piles of documents, understand what they say, and answer questions about them in plain English—without replacing the lawyers’ judgment.
This is like giving litigators a super-fast junior attorney who can skim millions of pages, highlight what matters for your case, and organize it for you in hours instead of weeks.
This is like giving every litigation team a super-fast junior attorney that can read thousands of documents, flag what’s relevant, explain why it thinks so, and show its work—so humans can make final calls much faster and with better evidence at hand.
Imagine having a tireless junior lawyer who can instantly read millions of emails, contracts, source code files and technical documents, then answer, “Show me everything related to this patent dispute and highlight the risky items,” in plain English. That’s what GenAI-powered e-discovery does for IP-heavy cases.
This is like giving Netflix a smart brain that quietly watches what you watch, when you stop, what you search for, and then rearranges the entire app, recommendations, images, and streaming quality just for you—millions of people at once, all differently.
This is about using tools like ChatGPT—tailored for lawyers—to draft documents, summarize long cases, search through legal information, and automate repetitive office work so law firms can focus more on clients and strategy.
Think of this as a checklist to see whether your eDiscovery software is a true legal “co-pilot” or just a smarter search bar. A truly intelligent platform doesn’t just find keywords; it understands documents, people, and issues, and helps you prioritize what matters most in a case.
This is about how Netflix-style “Because you watched…” lists are created. The system watches what you watch, when you stop, what you rewatch, and then predicts what you’re most likely to enjoy next—like a super‑attentive video store clerk who’s seen your entire viewing history.