Why Ropes & Gray Chose Draftwise: Turning Precedent Into Advantage

We are excited to announce that Ropes & Gray is a Draftwise customer. For a firm known for its disciplined approach to technology—investing only when solutions demonstrate clear, measurable value—this signals a significant milestone in the maturation of AI in legal practice and validates the vision we've been building toward. That vision is now a reality as Draftwise delivers on the promise of agentic AI grounded in institutional knowledge.

The real problem isn't LLMs—it's context

LLMs excel at summarizing, writing code, and brainstorming. Their tendency to hallucinate can spark creativity and exploration, but lawyers need precision, not plausibility.

This is precisely why we created purpose-built AI for legal work from day one. The problem is not LLMs themselves, but their training data. Would you stake your legal career on data from Reddit discussions and scraped web content, or even worse, hallucinations? While others have white-labeled GPT and promoted public data as revolutionary, we focused on what actually matters: institutional knowledge, decades of deal history, and client-favored terms that make each firm truly competitive.

Our answer: AI built on your data

Our platform learns from your firm's contracts, grounding LLMs in real-world legal contexts and integrating directly into existing workflows. Ropes & Gray's deployment proves that AI powered by institutional data can achieve the enterprise-grade reliability required by the most demanding legal institutions.

From early partnerships with firms like Gunderson Dettmer—who will roll out Draftwise agentic AI across their entire transactional practice this quarter—to implementations with half of the Vault 10, a third of the AM Law 100, and over half of the Seven Sisters, the pattern is clear: AI delivers meaningful results only when given the right data. Sophisticated firms understand this, which is why they choose Draftwise when precision matters.

Why we built Draftwise differently

As a product leader at Palantir, I learned that successful AI systems amplify human expertise by first understanding the domain in which they operate. 

At Draftwise, we built a system that thinks like lawyers and uses AI to accelerate it. Law firms hold mountains of data—deal history, market trends, and counterparty terms—yet lawyers rely on heroic memory or manual searches to access it.

The solution wasn't just unlocking this data but making it intelligent and accessible. Real adoption requires meeting lawyers where they work, so we built directly into Microsoft Word. It requires a depth of understanding to rival that of the most senior partners. To achieve this, Draftwise indexes across transactions, breaking them down to the clause and negotiation point and organizing everything to mirror how lawyers draft and review documents. We transform unstructured contract language into structured, searchable data designed around legal workflows, making it easy to find and reuse precedent.

This structured foundation guides AI with real legal context, rather than relying on LLMs to infer contract logic from scattered data. This enables lawyers to identify costly errors while freeing partners to focus on strategic counsel rather than supervising associates.

What this means for knowledge work

Legal contracts are just the beginning. Every knowledge domain operates differently and has its own specific requirements. Building meaningful AI requires understanding how professionals actually work before layering on intelligence.

We built Draftwise to address a real problem: the fundamental mismatch between what lawyers need and what general-purpose AI can deliver. That mismatch exists in every specialized field.

The evolution of AI won't be about building better LLMs. It will be about building better models of the world, then teaching those to AI to make them faster, more accessible, and more powerful.

The future belongs to companies that understand this distinction.

‍Draftwise agentic AI is now generally available to law firms globally. Watch the demo here.‍