This company provides litigation intelligence engineering by deploying agentic AI to reverse-engineer legal outcomes in patent disputes. Their platform analyzes a 2B+ entity graph integrating dockets, file wrappers, and technical literature to identify case vulnerabilities. The resulting intelligence reports offer source-linked findings to strengthen motions and guide litigation strategy for law firms and corporate counsel.
Funding
$7.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Corporations spend billions annually on litigation in the United States, yet critical legal decisions, such as whether to litigate or settle, are often made without data-driven insights. This reliance on traditional methods can lead to suboptimal outcomes and unnecessary expenses.
Solution
Ex Parte provides AI-powered decision support services that leverage machine learning and natural language processing to predict litigation outcomes. The platform analyzes legal data to provide clients with insights for making informed decisions on litigation strategy, settlement negotiation, and attorney selection. By quantifying the likelihood of success, Ex Parte aims to improve clients' chances of winning legal disputes and optimize their legal spending. The system functions as a "Moneyball" approach to legal strategy, providing a data-driven advantage.
Target Audience
The primary customers are corporations seeking to optimize their legal strategies and reduce litigation expenses through data-driven decision-making.
Features
- Litigation outcome prediction using AI and machine learning algorithms
- Natural language processing of legal documents to extract relevant information
- Data-driven insights for litigation strategy and settlement negotiation
- Predictive analytics for attorney selection based on case characteristics