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Introduction In today’s digital age, electronicdiscovery, or eDiscovery, plays a crucial role in the legal process. The vast amount of electronically stored information (ESI) makes it essential for legal professionals to adopt effective eDiscovery strategies for navigating the complex world of litigation.
E-discovery solutions , a significant part of legal tech, were estimated to be a multi-billion-dollar industry. The global e-discovery market size was projected to reach $17.32 Predictive Analytics: Machinelearning algorithms examine historical case data to predict legal outcomes.
In today’s digital age, electronicdiscovery, or eDiscovery, plays a crucial role in the legal process. The vast amount of electronically stored information (ESI) makes it essential for legal professionals to adopt effective eDiscovery strategies for navigating the complex world of litigation.
We are often asked if we incorporate artificial intelligence (“AI”) into our legal workflows and electronicdiscovery processes. In e-discovery, models can be tailored to a dataset such as Continuous Active Learning (CAL). Given this, there is no one-size-fits-all for the defensibility of AI.
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