Tanguy's and Mike's Respective Backgrounds and Path into Legal Tech: Tanguy is an engineer with advanced degrees (including an MBA) from MIT and experience in venture capital, notably early-stage investing in legal tech startups (one of such startups being Ironclad) Mike has a background that includes working at the Federal Reserve, McKinsey, and co-founding a company that applied AI in the insurance space. Mike’s experience with AI and legal/regulatory challenges contributed to starting Paxton. Paxton's Recent Award: Celebrated being one of the winners at the 2024 ABA Tech Show Startup Alley Paxton's Technology and Approach: Focuses on developing industry-specific, application-specific, and firm-specific legal language models for greater accuracy, response speed, and security. The data for model training includes public domain legal documents, emphasizing legal-specific training over general-purpose models. Paxton enables customization for firms by allowing connections to internal knowledge sources without training the model on client-specific data unless requested. Applications of Paxton: Legal Research: Provides access to laws, regulations, and court rulings across all states and federal levels. Document Drafting: Uses a vast corpus of legal documents to assist in drafting accurate first drafts of legal documents. Document Analysis: Offers document analysis and Q&A capabilities for large volumes of documents, ensuring data privacy and governance for firms. Use Case for Training Young Lawyers: Paxton aids in training younger lawyers by allowing them to ask questions and practice without fear of judgment, enhancing their learning and confidence. Future Roadmap: Paxton plans to develop more advanced language models, connect to more data sources, and execute multi-step workflows for synthesized answers from various data sources. Advice for Legal Tech Startups: Tanguy and Mike emphasize the importance of being customer-centric, seeking feedback, and iterating based on user input to improve and refine the product.