Robin AI is a leader in legal AI. Our Legal AI Assistant is used by hundreds of businesses globally to harness the power of generative AI for legal. We empower legal teams and lawyers to make contract processes effortless.
Pincites makes contract negotiations faster and more consistent for legal teams. Using advanced language models, Pincites allows legal teams to build robust contract playbooks that any internal team can apply consistently within Microsoft Word.
ThoughtRiver was founded in 2016 to transform third-party contract review. Over the past nine years, we’ve become a leader in the Legal Tech space, working with some of the world’s top legal teams and organizations. Our success is built on integrating human-led, legally trained data into our own LLM, ensuring accuracy and relevance in contract analysis.
Our AI-powered litigation tools open up a dialogue with your data, so your legal team can focus on what they do best: thinking.
Beagle is transforming how law firms, corporate legal teams, and eDiscovery service providers handle document review and eDiscovery. Our AI-powered platform delivers faster, more accurate results, streamlining processes and reducing costs to help you uncover key data quickly and efficiently.
Casetext is a legal research platform that uses artificial intelligence to help lawyers and legal professionals find relevant case law, statutes, and other legal materials efficiently. It was particularly known for its AI-powered tool, CARA (Case Analysis Research Assistant), which allowed users to upload legal documents and receive highly relevant case law recommendations.
RAND's analysis examines whether AI-generated works merit copyright protection and if training AI models on copyrighted content violates U.S. and international law. The research reveals emerging global divergence, with Beijing courts recognizing copyright for AI-generated images demonstrating human intellectual effort while U.S. approaches remain uncertain pending landmark litigation like NYT v. OpenAI. This comprehensive legal assessment provides critical insights for content creators and AI developers navigating the unresolved fair use questions that will determine billions in potential liability and the future of generative AI training practices.
RAND's policy analysis examines how AI algorithms' opacity creates fundamental privacy challenges around data collection, use, and decision-making, particularly in light of the EU AI Act's transparency requirements. The research explores regulatory approaches to address AI's lack of explainability while examining the tension between innovation and privacy protection under frameworks like GDPR and emerging U.S. state privacy laws. This authoritative government-sponsored research provides crucial insights for policymakers grappling with AI's transformative impact on privacy rights and the effectiveness of existing privacy legal frameworks.
FinTech Weekly's analysis contrasts global AI regulatory approaches, from the EU AI Act's comprehensive framework with €35 million penalties to China's strict government control versus Japan's flexible industry self-regulation. The piece examines Trump's pro-AI executive orders reversing Biden's 'safe and secure' AI policies while highlighting how financial services firms increasingly look to EU standards as 'best practice' despite compliance costs. This industry perspective illuminates the political volatility around AI regulation and the challenges facing financial services firms navigating divergent international regulatory philosophies.
Banking industry analysis reveals that while the EU AI Act establishes the world's first AI regulation in 2024, U.S. financial institutions face a 'fast-moving target' for compliance as regulatory frameworks remain unsettled. The assessment highlights SEC efforts to address AI conflicts of interest for investment advisors while emphasizing that loose regulatory frameworks create significant risks if AI isn't implemented diligently. This practitioner-focused piece underscores how compliance officers must monitor evolving AI requirements to protect data safety and security amid shifting national and global regulatory concerns.
Skadden's comprehensive analysis examines how the EU AI Act will govern financial services from 2024 while U.S. regulators rely on existing frameworks and guidance rather than new AI-specific legislation. The report details critical regulatory concerns including data quality, model risk, governance challenges, and consumer protection as 79% of UK financial firms have deployed machine learning applications beyond pilot phases. This authoritative assessment demonstrates the divergent regulatory approaches across jurisdictions and highlights the industry demand for harmonized international standards as financial institutions navigate complex compliance requirements.
Cooley's analysis reveals how Trump's reversal of Biden's AI policies eliminated federal guidance on workplace wearables and algorithmic bias, yet underlying anti-discrimination laws like Title VII and ADA remain fully applicable to AI systems. The piece emphasizes that while agencies removed AI-specific guidance documents, employers still face liability for discriminatory AI outcomes, particularly as state laws like Colorado's SB 24-205 impose additional AI compliance requirements. This practical legal assessment helps employers navigate the regulatory gap between federal policy shifts and persistent legal obligations in AI deployment.