ArbiLex

ArbiLex is a Harvard Law School-originated AI analytics platform for international arbitration and litigation finance, founded by CEO Isabel Yang. Uses Bayesian predictive analytics and machine learning to predict arbitration outcomes, assist with arbitrator selection (based on track record, time to resolution, appointment patterns), and quantify litigation risk. For lawyers, it provides arbitrator analytics; for funders, it provides AI-rated case pipelines with predicted outcomes. Core product is ArbiLex Funding Exchange (AFX), a subscription-based AI-rated case pipeline that rates new case filings in seconds. 500 Global portfolio company. Seed round June 2022. Extensively cited in academic literature on AI in arbitration (8+ papers, 2020-2025) and featured in Forbes, Harvard CLP, Legal Funding Journal. Claimed ‘successful tests by leading global law firms’ at 2019 Harvard Legal Tech Symposium, but no firm names disclosed. May operate primarily as a consulting/advisory service leveraging proprietary AI rather than a self-service software platform (CPR describes it as ‘AI-based litigation funding consulting firm’). Zero practitioner reviews or user testimonials found. Small team (2-10 employees, Boston HQ).

Who It’s For

• International arbitration practitioners who need data-driven arbitrator selection and outcome prediction
• Litigation funders evaluating high-stakes case pipelines at scale
• BigLaw and mid-size firm dispute resolution teams managing cross-border proceedings
• Tool appears to require demo access; not a self-service platform

What We Haven’t Verified

• Zero practitioner reviews or user testimonials found — all coverage is from press, academic papers, and industry events
• Website is JS-rendered — current pricing and detailed feature set not independently confirmed
• Model architecture, training data sources, and prediction accuracy metrics not publicly disclosed
• No security certifications (SOC 2, etc.) or data protection practices found — critical for litigation strategy data
• Number of active law firm clients and litigation funder subscribers unknown
• Jurisdictional and institutional coverage not specified (ICC, LCIA, SIAC, HKIAC, etc.)
• Whether founding team is still fully committed (one team member’s resume mentions micro1.ai)