Verbit, renowned for its expertise in transcription technology, has unveiled Legal Visor at Legalweek. This AI-driven platform is designed to supply real-time insights during depositions, providing a potential competitive advantage for legal professionals by pinpointing inconsistencies and offering actionable intelligence. Legal Visor integrates Verbit’s Captivate technology to deliver highly accurate transcriptions and further enhance its utility through domain-specific models tailored for legal jargon.
The platform’s features extend beyond just transcription; it connects with case materials to boost accuracy and generate insights. Key functionalities include inconsistency detection, which flags discrepancies between testimonies, and smart search capabilities that allow attorneys to employ semantic and generative queries within testimonies and documents. Furthermore, Legal Visor offers automatic speaker ID, supports over 50 languages, and features such as chaptering and summaries for streamlined review.
Developed in collaboration with law firms like Fisher Phillips and Smith, Gambrell & Russell, Legal Visor empowers second-chair attorneys by providing real-time insights that can be leveraged to inform strategies during depositions. Crucially, the platform is constructed to seamlessly integrate spoken content into existing legal workflows, generating a knowledge graph from both case documents and depositions to bring pertinent information to the forefront in real time. Legalweek attendees will be among the first to see the platform in action, with demonstrations scheduled at the event.
Looking forward, Verbit’s labs are working on future advancements such as sentiment analysis to ascertain emotions from speakers, and an analytical tool for scrutinizing body language and facial expressions during video testimonies. While Legal Visor opts for a user-based subscription model, the company remains open to adjusting this framework as they gauge client feedback and derive insights on where users perceive the most value.
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