AI Legal Drafting Assistant

Manual legal document review is an inefficient, time-consuming process. In an increasingly complex legal and regulatory environment, the length and quantity of documents is growing, compounding the cost of high-quality document review.

Our Legal Drafting Assistant uses frontier Generative AI to automate and optimize legal document workflows, enabling legal teams to handle a higher volume of contracts with increased efficiency and fewer bottlenecks. Select from a template library, automatically generate drafts, and chat with drafts to iterate on language. The assistant uses fine-tuned frontier models trained on your data and data from the Scale Data Engine to provide the most accurate and useful drafts. Work directly from the assistant UI, or in Microsoft Word or Google Docs via the assistant integrations.

• Automatically Generate Drafts
  Frontier Generative AI models are fine-tuned on your historical contracts, unique clauses, contractual preferences, and high-quality data from Scale Data Engine to generate high-quality drafts that require minimal revisions and dramatically reduce turnaround times.

• Real-Time Draft Iteration with Natural Language
  We fine-tune models on real draft iteration data from the Scale Data Engine enabling the assistant to easily add, replace, or modify clauses and terms with your natural language instructions. This empowers your team to make fast, accurate updates without the manual overhead.

• Seamless Integration with Your Preferred Tools
  Work where you’re most comfortable. Draft directly within the assistant’s intuitive interface, or take advantage of our deep integration with Microsoft Word and Google Docs through powerful plugins. Experience the ease of AI-assisted drafting without having to change your preferred workflow tools.

This powerful Generative AI solution was built with:

• Frontier generative models are fine-tuned with your legal contracts, playbooks, and high-quality legal data from Scale Data Engine to ensure high-quality generations.
• State-managed agentic workflows for reasoning across different document templates; these agents leverage chain-of-thought to ensure the accuracy of generated drafts; the agent checks its work along the way to minimize errors.
• Bespoke prompt engineering and turning, including in-context learning, few-shot learning, and task decomposition.