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Auto Predict Your Case Outcome and Case Research, and Perform Intensive Legal Analytics to Best Equip Yourself for Winning
eLegalls is a research-led legal tech startup, developed in Startup Factory (SUF) incubation at Iowa State University (ISU) in 2022. The core research idea was envisioned with intent to use technology to make a slow and expansive justice system better. eLegalls improves it at Lawyers’ level, who are the key maneuverers, players, and influencers in a justice system. More specifically, it speeds up the legal research and discoveries and significantly reduces the time required to manually search and review the previous case laws, in the view of assessing new cases brought before the court. For every new case, Lawyers and Law Firms manually do intensive case assessment and case discoveries, which take hours, weeks, and sometime months. eLegalls, which uses Artificial Intelligence (AI) technology to learn prior case laws, automates these tasks and helps them predict the case outcomes, the explanation behind such outcome, and case discoveries in just few seconds. The Lawyers and Judges can take the best advantages of eLegalls to predict the case outcomes to further augment their future course of actions, for example speeding up decision-making, support arguments, strengthening the defense, etc. eLegalls is trained and tested over large number of court cases and has achieved quite high accuracy.

How System Works:
Case prediction & research.The system provides a web interface to the end users for interaction and use. A legal expert can write the new case description or upload that as a pdf file to compute the predicted outcomes. In addition to the predicted judgment, a possible explanation (AI-generated opinion) behind the predicted decision is also to be reported in outcome. The system also renders the top ten prior case laws, most similar to the case at hand.

Legal analysis. The system also offers a legal analytics tool to the end user through an easy web interface. The user, legal expert, can perform several important analyses to quickly learn about the track record of the opposite counsel(s) through their past cases. The eLegalls' legal analytics also aids the end user to quickly learn about the presiding judge(s) through their records on prior case laws.

Overall, eLegalls equips and prepares a counsel for better strategic defense and win their case.

elegalls architecture

Research. eLegalls is committed to continuously engage in research and development activities to find new features to help strengthening the operations and outreach activities further. Some early research was recently published in the following articles:

1. Predicting Indian Supreme Court Judgments, Decisions, or AppealseLegalls Court Decision Predictor (eLegPredict)
2. Emerging Legal Informatics towards Legal Innovation: Current status and future challenges and opportunities
3. eLegalls: Enriching a Legal Justice System in the Emerging Legal Informatics and Legal Tech Era

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The model demonstartes around 80% accuracy. The likley outcome of your case is:



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10 most suitable prior case laws

  
Auto predict case outcome & case research to better prepare for best defense

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eLegalls' analysis- quickly learn more about your opponents and judge(s) through their prior case status logout
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Quickly learn about your opposite counsel and associated judge(s) through their prior cases

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Leadership Team

Business Advisor
Peter Hong
Mentor (SUF & G2M)
Legal Advisor
Jon Kallen
Domain advisor and mentor (G2M)
Business Advisor
John E. Derrick
Business advisor (VMS)



Business Development Advisor
Brandon Carlson
Business development advisor (VMS)
Technical Advisor
Ritu Shandilya, PhD
Technical advisor (Machine Learning)
Financial advisor
Tim Neugent
Financial advisor (SUF)



Founder/CTO
Sugam Sharma, PhD
Founder
CEO

Business development leader