Helping lawyers and law students work confidently with AI and open legal data
LegalText Lab is a hands-on research and development studio focused on practical, reliable AI for legal work. We build open tools, publish methods, and run experiments that make day-to-day legal research faster, safer, and more transparent—without sacrificing rigor.
Legal practice depends on authoritative sources, precise citations, and careful reasoning. Current AI tools are promising but often opaque, brittle, or hard to trust. We bridge that gap by combining open legal data with reproducible AI workflows, clear evaluation standards, and user-first design.
Turn plain English into structured API queries with safe defaults and error handling.
Compare keyword strategies, embeddings, and reranking to deliver results with pinned citations and confidence signals.
Detect treatments (followed, distinguished, overruled) and surface evidence, so you can quickly assess authority.
Orchestrate specialized agents (issue spotter, citation extractor, query planner) to support end-to-end tasks.
Train and evaluate open models for legal reasoning, and pair them with strong retrieval over case law and statutes.
Connect statutory sections to opinions with versioning and amendment-aware mapping.
CLI tools, evaluation harnesses, and example pipelines for research and teaching.
Transparent model comparisons for issue spotting, citation extraction, and reasoning quality.
Practical walkthroughs for fine-tuning, embedding selection, and multi-agent setups using open data.
Curated, versioned slices of case law and legislative text for reproducible experiments.
Prefer open models, data, and methods; document tradeoffs and limitations.
Every result ties back to sources; no ungrounded claims.
Clear metrics, test sets, and audit trails—so improvements are real, not anecdotal.
Guardrails against hallucinated citations; thoughtful handling of sensitive data in academic and practice contexts.
Learn modern AI research techniques with real legal data and workflows you can apply in clinics and journals.
Prototype faster research flows, integrate AI safely, and evaluate tools before they touch client work.
Collaborate on open datasets, model training, and evaluation standards for the legal domain.
Questions, collaborations, or pilot requests? Email admin@legaltext.ai and tell us what you're working on. We'll point you to the right tools—or help build them.