Explore AI technologies transforming legal — from Natural Language Processing to Large Language Models & Generative AI. Implementation examples, vendor comparisons, and real results.
NLP is the foundation of legal AI — enabling machines to read, understand, and extract meaning from contracts, case law, regulations, and other legal documents.
LLMs power a new generation of legal AI tools — Harvey, CoCounsel, Lexis+ AI — that draft documents, answer research questions, and analyze legal issues conversationally.
ML models power case outcome prediction, TAR document review, risk scoring, and pattern detection — learning from historical data to improve legal decision-making.
OCR digitizes scanned legal documents, handwritten notes, and historical records — making them searchable, analyzable, and processable by downstream AI systems.
RPA automates repetitive, rule-based legal workflows — document filing, data entry, system updates, and compliance reporting — freeing legal professionals for higher-value work.
Conversational AI powers client intake, internal legal help desks, self-service legal tools, and access-to-justice chatbots — making legal guidance more accessible and efficient.
Semantic search and RAG systems find relevant legal content based on meaning rather than keywords — powering legal research, clause search, and precedent retrieval with dramatically improved recall.
Analytics and BI tools transform legal data into actionable dashboards — tracking matter performance, outside counsel spend, contract metrics, and departmental KPIs in real time.
AI Roadmap — Associates spending the week on doc review. Contracts taking two weeks to turn. Both have AI fixes. We'll show you which, in what order. 72 hours.