Legal AI "Deal to Real"

Once contracts are signed, execution against terms is often inconsistent. Key obligations and deliverables get lost in long-form contracts, resulting in:

• Weak governance and compliance risks
• Missed opportunities for internal teams
• 9% value erosion during execution phase (industry studies)

The root cause: Complex legal language buried in lengthy contracts makes it difficult for teams to track and execute obligations effectively.

Designed an AI system that transforms contract execution:

Core Capabilities:

• Extracts and summarizes key obligations from contracts
• Structures obligations into digestible execution plans
• Surfaces progress tracking dashboards
• Flags risks early with intelligent alerts

Strategic Approach:

• Created differentiated product experiences for legal, business, and operations stakeholders
• Drove adoption among teams already stretched with manual processes
• Phased rollout starting with high-value contracts (>$500K)
• Built domain-specific legal language models for accuracy

Cross-Functional Partnership:

• Legal operations, engineering, data science, and UX design teams
• Led workshops with legal counsel, procurement, and business operations
• Conducted stakeholder interviews to understand workflow pain points
• Built internal champions across departments for adoption

Key Product Decisions:

Accuracy vs. Speed:

• Chose 95% accuracy with human-in-the-loop validation
• Over 99% accuracy with 10x processing time
• Justified by faster time-to-value for legal teams

Scope Prioritization:

• Prioritized high-value contract types first (>$500K)
• Rather than trying to handle all contract variations at launch
• Enabled focused learning and faster ROI

Challenges Navigated:

• Strict data privacy requirements (GDPR, confidential contract data)
• Integration complexity with existing CLM systems
• Change management for legal teams accustomed to manual processes
• Limited training data for specialized contract types
• Stakeholder buy-in from risk-averse legal counsel

Market Differentiation:

vs. DocuSign CLM & Ironclad:

• They focus on contract creation; we focus on post-signature execution
• Fills the gap where 9% value erosion typically occurs

vs. Generic AI Tools:

• Built domain-specific models for legal language
• Deep understanding of contract law and obligations
• Purpose-built for compliance tracking, not general Q&A

Key Learnings:

Learned the importance of phased rollouts and building trust with risk-averse stakeholders. Success came from focusing on augmentation rather than replacement of legal expertise.

What I'd Do Differently:

• Invest more time upfront in change management
• Create internal champions earlier in the process
• Start with even narrower use case for faster wins

Most Valuable Insight: Legal teams don't fear AI replacing them—they fear being held responsible when AI makes mistakes. Building in human validation loops was the key to adoption.