Briefpoint is a legal tech company that offers AI-powered software to automate and streamline the discovery process for legal professionals. It integrates with legal practice management software like Clio and Smokeball.
Docsum is an AI contract review and negotiation platform. With Docsum, legal, procurement, and sales teams can negotiate and manage contracts 3x faster, to reduce the time to close and win more deals. Docsum works by analyzing and redlining contracts using configurable playbooks owned by lawyers.
Recital is a legal tech company that utilizes AI to streamline contract management for in-house legal teams. It focuses on simplifying and accelerating the contract review process through features like clause extraction and suggestion, as well as automated contract organization and updates. Recital aims to address the challenges of growing workloads and tight deadlines faced by legal departments.
DocDraft is an AI-powered legal platform designed to assist small businesses and individuals with drafting legal documents. It offers features such as AI-powered document drafting, allowing users to generate customized legal documents in minutes, and aims to provide affordable, accessible, and customizable legal support. DocDraft utilizes AI to automate the creation of legal documents, streamlining the process and improving efficiency for legal professionals.
Syntheia automatically turns your contracts into data, and delivers that data where you need it, when you need it. Each of our apps is designed to fit existing workflows - reviewing documents, creating a clause bank, drafting documents and advice, and collaborating on work.
Lexis® Create+ leverages existing internal work products of legal professionals, delivering a powerful, personalized drafting experience in Microsoft 365. It is grounded in your firm’s DMS and authoritative LexisNexis® sources, with generative AI capabilities built right in. Connect the full knowledge of your firm with the unrivaled insights of LexisNexis for everything you need to quickly build exceptional legal documents while preserving firm confidentiality and privacy requirements.
AP News reports on UK High Court Justice Victoria Sharp's warning that lawyers citing AI-generated fake cases pose 'serious implications for the administration of justice and public confidence in the justice system.' The case highlights growing global judicial concerns about AI misuse in court proceedings, with judges threatening prosecution for attorneys who fail to verify AI-generated research accuracy. This breaking news story exemplifies the urgent need for regulatory frameworks and professional standards governing AI use in legal practice as courts worldwide grapple with maintaining integrity in an AI-enhanced justice system.
ABA's comprehensive legal analysis covers the busiest year in AI legal history, examining copyright battles between algorithmic infringement allegations and fair use defenses while tracking bias, transparency, and privacy litigation trends. The report details landmark cases including USA v. Michel, where criminal convictions involved experimental GenAI program usage, and emphasizes how trial courts are creating de facto AI legal rules absent comprehensive congressional regulation. This authoritative judicial overview demonstrates that judges and bar regulators are increasingly focused on ethical GenAI use rules as litigation shapes AI law development through case-by-case precedent.
Copyright Alliance's comprehensive litigation review tracks over thirty GAI copyright lawsuits including landmark cases like Andersen v. Stability AI and Kadrey v. Meta, with key developments including DMCA dismissals and fair use arguments by defendants. The analysis highlights critical 2024 court rulings that hint at judicial leanings while noting the consolidation of similar cases and the high-stakes nature of these disputes for both creators and AI developers. This detailed case tracking demonstrates how copyright litigation will be pivotal in shaping GAI's future, with courts beginning to address fundamental questions about training data use and fair use defenses.
ABA Journal's technology analysis reveals that 2024 marked a year of contradictions, with rapid AI integration into legal technology that remained largely surface-level despite unprecedented software update rates from vendors. The assessment details how AI transformed deposition analysis, brief drafting, pretrial discovery, and law practice management while noting that usage stabilized after initial rapid adoption. This practitioner-focused review emphasizes the ongoing challenges of leveraging accessible data for analytics and high costs of mainstream AI models, while highlighting AI's growing impact on litigation strategy and case management efficiency.
GWU Law's comprehensive litigation database tracks ongoing and completed AI cases from complaint forward, covering everything from algorithmic bias in hiring and criminal sentencing to autonomous vehicle liability and AI authorship disputes. This unique academic resource provides broad coverage of AI legal disputes including statistical analysis and data protection cases relevant to AI projects, serving as a critical research tool for understanding litigation trends. The database demonstrates the rapidly expanding scope of AI-related legal challenges across multiple domains and its systematic documentation reveals patterns in how courts are addressing novel AI legal questions.
White & Case's regulatory tracker reveals that over 40 state AI bills were introduced in 2023, with Connecticut and Texas enacting AI discrimination assessment statutes, while federal agencies apply existing authorities like the FTC's Rite Aid facial recognition settlement. The analysis highlights how comprehensive state privacy laws like California's CPPA and Illinois's biometric privacy act create overlapping AI compliance requirements, demonstrating the complex regulatory patchwork facing businesses. This authoritative legal tracking emphasizes the practical enforcement reality that existing civil rights, privacy, and consumer protection laws fully apply to AI deployment despite the absence of comprehensive federal AI legislation.