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Ex Parte Raises $7.5M in Series A Financing

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Ex Parte, a legal tech startup, has secured $7.5 million in Series A funding led by R8 Capital and Ironbound Partners. The funds will enhance its engineering team and sales initiatives to boost customer acquisition. Ex Parte utilizes AI and machine learning to predict litigation outcomes with 85% accuracy, offering recommendations for legal strategies. The legal sector, spending over $250 billion annually on litigation, has been slow to adopt technological advancements, but Ex Parte aims to transform this outdated landscape.

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  • Raised $7.5 million in Series A financing to enhance engineering and marketing efforts.
  • Utilizes patented AI technology with 85% accuracy for predicting litigation outcomes, offering strategic recommendations.
  • Targets a lucrative market with over $250 billion spent on litigation annually.
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Legal Tech SaaS Startup using AI and ML to Predict and Optimize Litigation Outcomes

All-Star Investment Syndicate

“Moneyball for Law”

BETHESDA, Md.--(BUSINESS WIRE)-- Ex Parte, a pioneer in data-driven decision-making in the field of law, today announced it has raised $7.5 million in Series A financing. The round was led by R8 Capital, an investment firm founded by Bruce Rauner, the 42nd governor of Illinois and former chairman of private equity firm GTCR, and Ironbound Partners, led by Jonathan Ledecky, business entrepreneur and co-owner of the New York Islanders. The Company will use the capital to expand its engineering team and invest in sales and marketing initiatives to further scale new customer growth. Ex Parte’s customers and prospects include corporations, hedge funds, law firms, insurance companies, litigation finance firms, and universities.

Each year, corporations spend over $250 billion on litigation in the US equaling approximately 33% of Fortune 500 after-tax profits. However, critical legal decisions are largely made the same way they were 100 years ago. Every major industry, from finance and telecom to insurance and manufacturing, has been transformed by the big-data revolution, but the field of law has lagged far behind.

Ex Parte is the world’s first company to leverage artificial intelligence and machine learning to predict the outcome of litigation and recommend actions that its customers can take to optimize their odds of winning. The company’s patented Prediction Engine™ forecasts the outcome of cases with approximately 85% accuracy, and its patented Recommendation Engine™ generates data-driven recommendations such as whether to litigate or settle, which claims to assert, where to file or defend a lawsuit, and which attorneys and law firms will provide customers with their best chance of success given their case-specific factors.

“There are many technical and conceptual challenges associated with building a robust model of a lawsuit,” said founder and CEO Jonathan F. Klein. “Legal data is by its nature disparate, unstructured, and semantic. We have solved these problems by combining a highly specialized understanding of the legal field with advanced expertise in artificial intelligence, machine learning, and natural language processing.”

“Our mission is to be the leading worldwide provider of data-driven decision-making solutions in the field of law and provide our customers with a winning advantage,” continued Mr. Klein. “Think of us like Moneyball, but for a market more than 20x the size of Major League Baseball. We are grateful for the support of our incredible investors, which will allow us to accelerate our growth plans and fulfill our ambitious mission.”

Joining Gov. Rauner and Mr. Ledecky in the financing round are an all-star group of co-investors, including: Jeong Kim (executive chairman, Kiswe Mobile & former president, Bell Labs); Viet Dinh (chief legal & policy officer, Fox); Craig Coben (co-head global capital markets & former vice-chairman, Bank of America Merrill Lynch); Allen Morgan (founder & CEO, Idealab NY); Auren Hoffman (CEO, SafeGraph); Mark Ein (CEO, Venturehouse Group); Keith Lemer (CEO, WellNet); Thomas Spahr (president, Libra Ventures); Wolf Ruzika (chairman, EastBanc Technologies); Brett Bossung (co-founder, Silverpeak); Richard Wiedis (partner, Diaz, Reus & Targ); and Gregory Lubar (vice chairman, JLL).

Prior to founding Ex Parte, Mr. Klein was president & chief legal officer of MicroStrategy (Nasdaq: MSTR), the largest independent publicly-traded analytics and business intelligence company. Before MicroStrategy, he served as an appellate litigator with the United States Department of Justice, and a law clerk for the Hon. Jerome Farris of the United States Court of Appeals for the Ninth Circuit. Mr. Klein received a B.A. in Economics from Amherst College and J.D. from Harvard Law School.

About Ex Parte

Ex Parte is a software-as-a-service (SaaS) legal-tech company headquartered in the Washington, DC area that uses artificial intelligence and machine learning to predict the outcome of litigation and recommend actions that customers can take to optimize their odds of winning. Our customers and prospects include corporations, hedge funds, law firms, insurance companies, litigation finance firms, and universities. For more information, please visit www.exparte.com.

Media Contacts:

Alex Jeffrey/Justin Dechiario

Gasthalter & Co.

(212) 257-4170

Source: Ex Parte

FAQ

What is Ex Parte's latest funding announcement regarding MSTR?

Ex Parte announced it raised $7.5 million in Series A financing to expand engineering and marketing efforts.

How does Ex Parte leverage AI in its services related to MSTR?

Ex Parte uses AI and machine learning to predict litigation outcomes and provide data-driven recommendations.

What is the estimated annual spending on litigation that Ex Parte targets?

Corporations spend over $250 billion annually on litigation in the US.

Who led the Series A funding round for Ex Parte?

The Series A funding round was led by R8 Capital and Ironbound Partners.

What is the accuracy of Ex Parte's litigation outcome predictions?

Ex Parte's Prediction Engine forecasts litigation outcomes with approximately 85% accuracy.

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