Litera
The unified legal document lifecycle and transaction management ecosystem for the modern law firm.
Enterprise-grade predictive legal analytics for high-stakes litigation and risk assessment.
CaseCrunch is a sophisticated legal decision-making platform that leverages high-dimensional natural language understanding (NLU) and legal knowledge graphs to predict the outcomes of legal disputes. Unlike standard LLMs that generate text, CaseCrunch's architecture is specifically tuned for 'Outcome Prediction'—a process where the system evaluates historical case law, jurisdictional trends, and specific evidentiary parameters to provide a probability-based forecast of success. By 2026, the platform has evolved from its famous 'Man vs. Machine' challenge roots into a robust enterprise solution for insurance companies and global law firms. Its technical core utilizes a proprietary Ensemble Learning model that mitigates the 'black box' problem by providing explainable AI (XAI) justifications for every risk score. This allows legal departments to automate the triage of thousands of claims, identifying which to settle and which to litigate based on quantitative data rather than qualitative intuition. The platform's 2026 market position is solidified as a mission-critical tool for ESG compliance and regulatory risk forecasting in the UK and EU markets.
Provides a human-readable trace of the factors leading to a specific prediction, referencing exact precedents.
The unified legal document lifecycle and transaction management ecosystem for the modern law firm.
The AI-powered litigation lifecycle platform for smarter case strategy and automated chronologies.
The infinite workspace for deep document analysis and multi-source synthesis.
Enterprise-grade eDiscovery and AI-driven document intelligence for boutique and mid-market law firms.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Dynamically weights the relevance of past rulings based on temporal proximity and judicial seniority.
Analyzes the tone and linguistic consistency of opposing counsel's filings.
Visualizes success rates across different courtrooms and specific judges.
Connects structured legal databases with unstructured claim text via RDF triples.
Uses risk scores to automatically route high-exposure claims to senior partners.
Simulates 'What If' scenarios by altering specific case variables to see outcome shifts.
Manual review of thousands of PPI or motor claims is slow and inconsistent.
Registry Updated:2/7/2026
High-risk claims are flagged for manual legal review.
Identifying hidden litigation risks in thousands of a target company's contracts.
Ensuring company policies align with rapidly changing financial regulations.