E-Discovery & Document Review
Posted: Mon Jul 20, 2026 12:33 pm
E-Discovery & Document Review
E-discovery platforms manage the collection, processing, review, and production of documents and data in litigation, investigations, and regulatory matters, and AI has become central to making that review affordable at scale. Predictive coding uses machine learning to rank documents by relevance based on a reviewer's early coding decisions, so the system continuously re-prioritizes what a human reviews next; generative-AI layers on top of that (such as Relativity's 'aiR' or Everlaw's AI assistant) can summarize documents, answer open-ended questions across a data set with citations back to specific documents, and flag privileged material before it is produced — tasks that used to require armies of contract attorneys billing by the hour. Pricing in this category is usually driven by data volume (dollars per gigabyte hosted per month) plus a platform or user fee, which means costs can spike unpredictably on data-heavy matters; several vendors have begun offering fixed-fee AI review pricing specifically to remove that uncertainty. The category spans from enterprise-grade platforms built for the largest law firms and government agencies down to simplified, self-service tools aimed at smaller matters and tighter budgets, so the right choice depends heavily on matter size and whether the legal department has (or wants to pay for) a dedicated e-discovery administrator.
E-discovery platforms manage the collection, processing, review, and production of documents and data in litigation, investigations, and regulatory matters, and AI has become central to making that review affordable at scale. Predictive coding uses machine learning to rank documents by relevance based on a reviewer's early coding decisions, so the system continuously re-prioritizes what a human reviews next; generative-AI layers on top of that (such as Relativity's 'aiR' or Everlaw's AI assistant) can summarize documents, answer open-ended questions across a data set with citations back to specific documents, and flag privileged material before it is produced — tasks that used to require armies of contract attorneys billing by the hour. Pricing in this category is usually driven by data volume (dollars per gigabyte hosted per month) plus a platform or user fee, which means costs can spike unpredictably on data-heavy matters; several vendors have begun offering fixed-fee AI review pricing specifically to remove that uncertainty. The category spans from enterprise-grade platforms built for the largest law firms and government agencies down to simplified, self-service tools aimed at smaller matters and tighter budgets, so the right choice depends heavily on matter size and whether the legal department has (or wants to pay for) a dedicated e-discovery administrator.