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Vlex Pushes Legal Tech Boundaries with New Features and Top Talent

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Manage episode 412815173 series 3068634
Content provided by Greg Lambert & Marlene Gebauer, Greg Lambert, and Marlene Gebauer. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Greg Lambert & Marlene Gebauer, Greg Lambert, and Marlene Gebauer or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Our friend Damien Riehl stopped by to talk with Marlene Gebauer about two big happenings at vLex. Riehl unveiled exciting advancements in vLex's AI-powered legal research platform and shed light on vLex's commitment to streamlining legal workflows and reducing the need for extensive prompt engineering.

One of the major developments is the enhanced document analysis feature. Users can now upload legal documents, such as complaints, and vLex's AI will automatically extract key information including claims, facts, parties involved, and potential legal defenses. This eliminates the tedious manual process of reviewing and analyzing documents, saving lawyers significant time and effort. Additionally, the platform suggests relevant legal research questions based on the document's content, further expediting the research process.

vLex's advancements directly address the growing concerns surrounding prompt engineering in legal tech. By automating key analytical tasks, the platform empowers lawyers to focus on higher-level strategizing and client interactions, rather than spending hours crafting the perfect prompts for AI tools. Riehl echoes the sentiment of OpenAI's Sam Altman, believing that successful AI integration should render prompt engineering obsolete. He acknowledges that the option to fine-tune prompts remains, similar to Boolean search techniques, but emphasizes that vLex aims to make it a choice rather than a necessity.

The potential impact on the legal industry is substantial. Clients, especially large corporations, can leverage vLex's capabilities to analyze past legal actions and assess the value provided by their law firms. This transparency could lead to a shift from billable hours to flat-fee arrangements, incentivizing efficiency and cost-effectiveness.

Further amplifying vLex's potential, the company welcomes Daniel Hoadley, a renowned legal tech expert, to lead their research and development team. Hoadley's expertise in data science and large language models promises exciting advancements in harnessing the power of vLex's vast legal document database. With a robust roadmap of projects, vLex's is poised to continue pushing the boundaries of legal technology and shaping the future of legal practice.

Listen on mobile platforms: ⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠ | ⁠⁠⁠⁠Spotify⁠⁠⁠⁠ | ⁠⁠⁠YouTube⁠⁠

Contact Us:

Twitter: ⁠⁠⁠⁠⁠@gebauerm⁠⁠⁠⁠⁠, or ⁠⁠⁠⁠⁠@glambert
⁠⁠⁠⁠⁠Threads: @glambertpod or @gebauerm66
Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠

  continue reading

253 episodes

Artwork
iconShare
 
Manage episode 412815173 series 3068634
Content provided by Greg Lambert & Marlene Gebauer, Greg Lambert, and Marlene Gebauer. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Greg Lambert & Marlene Gebauer, Greg Lambert, and Marlene Gebauer or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Our friend Damien Riehl stopped by to talk with Marlene Gebauer about two big happenings at vLex. Riehl unveiled exciting advancements in vLex's AI-powered legal research platform and shed light on vLex's commitment to streamlining legal workflows and reducing the need for extensive prompt engineering.

One of the major developments is the enhanced document analysis feature. Users can now upload legal documents, such as complaints, and vLex's AI will automatically extract key information including claims, facts, parties involved, and potential legal defenses. This eliminates the tedious manual process of reviewing and analyzing documents, saving lawyers significant time and effort. Additionally, the platform suggests relevant legal research questions based on the document's content, further expediting the research process.

vLex's advancements directly address the growing concerns surrounding prompt engineering in legal tech. By automating key analytical tasks, the platform empowers lawyers to focus on higher-level strategizing and client interactions, rather than spending hours crafting the perfect prompts for AI tools. Riehl echoes the sentiment of OpenAI's Sam Altman, believing that successful AI integration should render prompt engineering obsolete. He acknowledges that the option to fine-tune prompts remains, similar to Boolean search techniques, but emphasizes that vLex aims to make it a choice rather than a necessity.

The potential impact on the legal industry is substantial. Clients, especially large corporations, can leverage vLex's capabilities to analyze past legal actions and assess the value provided by their law firms. This transparency could lead to a shift from billable hours to flat-fee arrangements, incentivizing efficiency and cost-effectiveness.

Further amplifying vLex's potential, the company welcomes Daniel Hoadley, a renowned legal tech expert, to lead their research and development team. Hoadley's expertise in data science and large language models promises exciting advancements in harnessing the power of vLex's vast legal document database. With a robust roadmap of projects, vLex's is poised to continue pushing the boundaries of legal technology and shaping the future of legal practice.

Listen on mobile platforms: ⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠ | ⁠⁠⁠⁠Spotify⁠⁠⁠⁠ | ⁠⁠⁠YouTube⁠⁠

Contact Us:

Twitter: ⁠⁠⁠⁠⁠@gebauerm⁠⁠⁠⁠⁠, or ⁠⁠⁠⁠⁠@glambert
⁠⁠⁠⁠⁠Threads: @glambertpod or @gebauerm66
Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠

  continue reading

253 episodes

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