Global Pharmaceutical Company

A global pharmaceutical company faced a contract management crisis driven by sustained business growth. With legal and contracting operations distributed across Denmark (headquarters), Netherlands, and India Global Business Services, the organization managed three distinct contracting models simultaneously: headquarters where business users created contracts independently using templates, center of excellence handling most contract creation inquiries, and fully centralized operations routing everything through legal.

The entire contract lifecycle operated through manual, paper-based processes coordinated via Outlook email chains. Legal teams created contracts in Word, circulated drafts for peer review via email, sent agreements to vendors via email, received vendor markups via email, and manually reworked documents to address concerns. This email-dependent workflow created significant inefficiency, human error, lack of audit trails, and zero visibility into contract status once agreements entered the review process.

The organization's existing playbooks for Master Service Agreements and other contract types had become outdated and were inconsistently applied across regions and users. More critically, they lacked any measurable enforcement mechanisms or data-driven insights into negotiation patterns. Legal teams had no visibility into which clauses were genuinely negotiated versus routinely accepted by vendors, leading to inefficient allocation of legal time on clauses that might not require expert attention.

With contracts stored across multiple disparate systems—SharePoint for working documents, Coupa for signed agreements, and various business unit repositories—the organization struggled with basic contract intelligence. Users couldn't find contracts after storage because search depended entirely on metadata quality from contract owners during upload. The organization needed deep text analysis capabilities that could go beyond surface-level metadata to understand actual contract language, identify clause variations, assess quality differences across decentralized creators, and reveal patterns across their portfolio.

Constant pressure from lines of business for faster contract turnaround created friction in vendor relationships and delayed downstream business processes. Legal teams across all three geographies were overwhelmed with time-intensive manual review, while the lack of transparency in contracting timelines prevented proactive workload management and created unpredictable service delivery to internal customers. The organization explicitly rejected headcount growth as a scaling solution, seeking instead a sustainable, technology-enabled approach to handle increasing contract volume.

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The organization's innovation hub in India initiated the search for AI-powered contract intelligence capabilities in early 2024. As the business case became apparent, the initiative escalated from a local India project to a global evaluation controlled by headquarters—demonstrating executive-level recognition of the strategic importance of solving their contract management challenges.

The organization needed a comprehensive solution that could address their complete contract lifecycle, not point solutions for isolated problems. They required AI capabilities spanning contract discovery (finding agreements in fragmented repositories), data extraction (pulling intelligence from unstructured content), automated drafting (accelerating initial contract creation from templates), and AI-powered redlining (identifying vendor deviations from standards and proposing alternative language).

Given their pharmaceutical industry regulatory environment, the solution needed to meet rigorous compliance requirements. IT security teams would conduct comprehensive risk assessments on the AI platform, data hosting approach, and model training using sensitive contract data. Quality assurance teams needed to approve data usage for AI training, particularly concerning financial information and pharmaceutical regulatory content in contracts. The vendor would need to demonstrate pharmaceutical industry validation through relevant case studies and client references showing they understood regulatory compliance requirements, complex contract types, and pharmaceutical terminology.

Integration capabilities mattered significantly. The organization wanted a solution that could integrate with their existing technology investments—Coupa for procurement and spend management, DocuSign for e-signatures, and potentially their custom-built CLM system—to minimize disruption while adding an intelligence layer their current tools lacked. However, they remained open to complete platform replacement if a vendor demonstrated exceptional value that justified overcoming sunk cost considerations.

The organization defined three primary success criteria upfront: measurable time savings through quantified reduction in lawyer hours spent on contract review, enhanced user experience that would drive adoption without creating new complexity for decentralized contract creators, and improved contract quality through consistent application of company positions across all regions. Beyond basic efficiency, they sought negotiation analytics that could reveal which clauses genuinely required legal attention versus those that could be automated or delegated—enabling smarter resource allocation and strategic prioritization.

The organization followed a structured evaluation methodology typical of their enterprise software procurement: detailed user journey mapping with business stakeholders to identify gaps, definition of 3-4 specific KPIs the solution must address, and competitive assessment across multiple vendors. They explored Harvey AI (demonstrated by PwC), engaged consulting firms including KPMG for procurement-focused AI applications, and evaluated several other CLM platforms simultaneously. The evaluation included a February 2025 workshop focused on Master Service Agreements as the initial use case, testing 5-6 critical clauses to validate whether AI could replicate their legal thinking and deliver promised capabilities.

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The organization selected Leah platform after rigorous competitive evaluation, choosing it over Harvey AI and multiple other vendors for several compelling reasons that aligned with their pharmaceutical industry requirements and strategic objectives.

Comprehensive AI Capabilities Across the Complete Lifecycle: Leah offered robust functionality spanning all four critical AI capabilities required—contract discovery, data extraction, automated drafting, and AI-powered redlining. Unlike point solutions addressing isolated problems, Leah provided an integrated platform where these capabilities worked together to deliver interconnected value.

Multi-LLM Architecture and Technical Differentiation: Leah approach to leveraging multiple large language models rather than relying on a single AI engine resonated as a technical advantage. This architecture provided the flexibility and accuracy pharmaceutical compliance required, with the ability to select optimal models for specific contract analysis tasks while maintaining guardrails and verification mechanisms critical in a high-stakes regulatory environment.

Pharmaceutical Industry Validation and Compliance: Leah demonstrated sufficient pharmaceutical industry experience through relevant case studies and client references, proving they understood regulatory compliance requirements, complex contract types (employment agreements, M&A, pharmaceutical regulatory agreements), and industry-specific terminology. The vendor successfully addressed concerns about false positives, accuracy metrics, and AI transparency—critical considerations where missing contract terms could have serious compliance implications.

Azure Cloud Infrastructure with Data Sovereignty: The proposed Azure-hosted workshop environment (Amsterdam or Dublin data center) with options for private cloud hosting in the organization's own infrastructure post-evaluation aligned perfectly with pharmaceutical data sovereignty concerns and security requirements. This flexibility on hosting demonstrated understanding of enterprise compliance needs without compromising on platform capabilities.

User Experience Design that Drove Adoption Confidence: Initial demo attendees from legal teams across all three geographies responded very positively to Leah platform's visual design and intuitiveness. Team members expressed confidence they could adopt the solution easily for daily work—a critical validation given the decentralized user base with varying technical sophistication and the organization's emphasis on user experience as a success metric. This enthusiasm addressed their primary concern about complexity creating adoption barriers.

Playbook Discipline and Negotiation Analytics: Beyond basic automation, Leah platform would enable the strategic insights the organization sought around negotiation patterns and playbook optimization.

The solution would allow them to gather data revealing which clauses were genuinely negotiated versus routinely accepted by vendors, enabling smarter resource allocation and documentation of strong fallback positions for various contract terms. This strategic use case differentiated Leah from competitors focused purely on efficiency rather than negotiation intelligence.

Multi-Regional Deployment Flexibility: The platform's ability to accommodate three distinct contracting models across geographies—from headquarters' independent business user creation to center of excellence support to centralized legal operations—demonstrated solution flexibility that competitors lacked. This capability to serve diverse workflows without forcing organizational standardization proved critical for a global pharmaceutical company with legitimate regional variations.

Partnership Approach and Implementation Support: Leah willingness to engage executive leadership in workshop planning, advocate for in-person delivery where the framework-building team was located, and work collaboratively on POC structure demonstrated a partnership mentality rather than transactional vendor relationship. This approach aligned with the organization's sophisticated procurement culture and need for hands-on implementation support.

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