An Enterprise Analytics Company Unlocks Previously Impossible 7-10 Year Contract Generation with Leah
An enterprise analytics company, a global business intelligence and analytics software company, faced a critical technical limitation blocking their highest-value enterprise deals. Their sales order form template architecture contained 28 separate tables, each requiring individual API calls to populate contract data. This created severe performance bottlenecks—contracts took 30+ seconds to load when instant generation was expected.
Printable versions of seven-year and ten-year enterprise agreements could be generated
Contract requests processed monthly by the legal department
Separate API calls required for each contract, creating extreme performance degradation
“We just needed a solution that could handle the complexity of our enterprise agreements without the performance penalties that were preventing us from closing deals.”
Implementation Lead, An Enterprise Analytics Company
Challenge
An enterprise analytics company, a global business intelligence and analytics software company, faced a critical technical limitation blocking their highest-value enterprise deals. Their sales order form template architecture contained 28 separate tables, each requiring individual API calls to populate contract data. This created severe performance bottlenecks—contracts took 30+ seconds to load when instant generation was expected.
Most critically, the system couldn't generate printable versions of their longer-term contracts at all, directly blocking the company's ability to close large enterprise opportunities. This wasn't a minor inconvenience—it was a deal-blocking technical limitation on their highest-value agreements.
The legal department experienced additional resource pressures following significant staffing reductions, creating intense urgency to implement automation tools that could handle high contract volumes with reduced capacity. The Chief Legal Officer was eager to deploy efficiency capabilities, with the legal team negotiating contracts extensively throughout each day.
Their legacy contract management approach lacked modern generative AI capabilities for contract review and redlining. Competing CLM vendors evaluated could only strike entire clauses rather than perform surgical edits—changing specific words or phrases—which didn't match the organization's sophisticated negotiation requirements. The team needed a solution that could understand their specific playbook positions on governing law, limitation of liability, and other standard clauses without requiring manual review of every provision.
Solution Search
An enterprise analytics company selected Leah CLM with Leah Agentic AI Platform for its differentiated capabilities that competing solutions couldn't match. The platform's surgical AI redlining—the ability to change specific words or phrases rather than striking entire clauses—was explicitly cited as a primary selection criterion that eliminated competitors from consideration.
The solution provides comprehensive contract lifecycle management capabilities including:
Advanced Document Generation: Dynamic tables technology that consolidates complex template structures into streamlined architectures, reducing API call requirements while maintaining sophisticated document generation capabilities for multi-year enterprise agreements.
AI-Powered Contract Intelligence: Leah’s platform with automated contract review, risk assessment, and intelligent redlining that makes precise word-level edits rather than blanket clause deletions. Custom AI models can be trained on company-specific documents and playbooks rather than relying on generic templates.
Playbook Automation: The system encodes legal playbook rules in plain English for automated compliance checking, ensuring consistent application of negotiation positions across all contract reviews regardless of which team member is handling the agreement.
Enterprise Integration: Deep integration capabilities with Salesforce and other enterprise systems, supporting high-volume data flows and complex workflows across distributed global teams.
The platform's ability to create custom AI redlining models trained on the organization's specific master service agreement and legal playbook ensured the AI understood their unique negotiation positions and could automatically flag deviations without generic guidance.
“This feature is a game changer. It makes the platform more modernized and more flexible, giving our team a great deal of flexibility on how we design templates going forward.”
Implementation Lead, An Enterprise Analytics Company
Implementation
An enterprise analytics company began Leah CLM implementation in mid-2024, with the system going live in October 2024. The legal team led a comprehensive vendor evaluation focused on surgical redlining capabilities, custom AI model training, Salesforce integration quality, and day-to-day usability for legal professionals.
The deployment followed a phased approach: Phase 1 focused on core CLM functionality with a limited document set, while Phase 2 expanded to Leah playbook capabilities, additional document types, and legacy contract migration of up to 15,000 records. The implementation involved coordination across legal, RevOps, sales, and IT teams to establish workflows from draft creation through legal review, RevOps approval, and final execution.
The company experienced significant technical challenges during December 2024—their critical year-end period when contract volume peaks. System stability issues required immediate vendor escalation with daily problem-solving meetings and 24/7 support coverage throughout the quarter-end period. Leah’s engineering teams conducted bundle deployments and re-architected API interactions, completing the technical resolution in March 2025.
A key breakthrough came through collaborative innovation between the company and Leah’s product development team. Recognizing the performance limitations of the 28-table architecture, the teams co-developed dynamic tables functionality specifically designed to address these enterprise-scale challenges. The vendor provided systematic planning support for legacy contract migration, including templates for data organization, metadata review processes, and batch file transfers.
By early 2025, operations had stabilized and the team successfully deployed Leah’s platform capabilities faster than originally expected. The implementation demonstrated the vendor's commitment to working through complex enterprise deployment challenges rather than abandoning difficult technical requirements.
Outcome
The dynamic tables feature, deployed in June 2025, transformed an enterprise analytics company's contract operations with measurable architectural and performance improvements. The technology consolidated their sales order form from 28 separate tables down to just 5 dynamic tables, fundamentally changing the system's data architecture. This redesign reduced API calls from 28 individual requests to a single unified call—a 96% reduction in API complexity.
Most significantly, the architectural transformation unlocked previously impossible capabilities. The company successfully generated and printed seven-year and ten-year enterprise agreements that the old architecture simply couldn't produce, removing a critical blocker on their highest-value sales opportunities.
The platform now processes 1,093+ contract requests monthly across multiple document types including sales order forms, NDAs, amendments, statements of work, and complex multi-year enterprise agreements. The system serves as embedded operational infrastructure across legal, RevOps, and sales teams rather than a pilot deployment.
The resource-constrained legal department successfully handles high contract volumes despite reduced staffing through AI-powered automation. Leah's playbook configuration enables automated contract intelligence and risk assessment, reducing the manual clause-by-clause review that previously consumed legal capacity.
The organization expanded from 50 to 70 user licenses as adoption grew, demonstrating continued investment despite implementation challenges. The team accelerated legacy contract migration efforts, planning completion of a substantial portion of their 15,000+ contract records by mid-2025.
"This represents a huge win from our partnership perspective. The innovation benefits not just us but I think a lot of the customer base seeking flexible document generation capabilities."
— Implementation Lead, the company
The co-innovation partnership demonstrates how collaborative product development can deliver breakthrough outcomes that solve customer-specific challenges while advancing platform capabilities for the broader user base. The company now views their CLM platform as essential operational infrastructure with the architectural flexibility to support increasingly sophisticated contract scenarios as their business evolves.
