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AstraZeneca’s Journey to Become Information-Driven with Cognitive Search
When Search Becomes a Strategic Asset
Most enterprises have search. Few have made it strategic. There is a significant difference between a search box that helps employees navigate a SharePoint intranet and a cognitive search platform that actively surfaces insight, connects expertise, monitors competitive signals, and learns from how knowledge workers interact with information every day.
AstraZeneca — one of the world’s leading biopharmaceutical companies, with over 80,000 employees and R&D operations spanning dozens of countries — made that transition. This webinar is the story of how they did it: the architectural decisions, the deployment journey, the organizational challenges, and the vision for what enterprise cognitive search looks like at true scale.
It is also a broader conversation about why cognitive search is rapidly becoming one of the most strategically important technology investments an enterprise can make — and what it takes to get it right.
Beyond the Intranet: How Cognitive Search Delivers Enterprise-Wide Intelligence
Many organizations invest in search—but stop at a single search box on the intranet. While enterprise search can connect silos of information, limiting it to basic navigation leaves significant value untapped.
In this 40-minute session, discover how leading enterprises move beyond traditional intranet search to unlock greater insight, operational efficiency, and competitive advantage using a cognitive search and analytics platform.
How AstraZeneca Built Cognitive Search at Enterprise Scale
Steve Sale, Search and Taxonomy Architect at AstraZeneca, shares how the organization designed and scaled cognitive search to support global knowledge access and decision-making. You’ll learn:
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The origins of cognitive search at AstraZeneca
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Key implementation steps—from pilot to enterprise-wide deployment
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How cognitive search expanded beyond isolated use cases
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The future roadmap for cognitive search across the organization
Why Cognitive Search Is Becoming a Strategic Enterprise Platform
In the second part of the session, Graham Charlesworth, Senior Manager in Accenture’s Content Analytics Group, and Martin Saunders, Senior Solution Consultant at Sinequa, explore the broader enterprise perspective. They cover:
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The current state of enterprise search and analytics
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Why large organizations across all industries need cognitive search platforms
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How AI-powered search transforms knowledge access, analytics, and decision-making
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The value of the Accenture–Sinequa partnership in delivering scalable, successful cognitive search initiatives
The Accenture–Sinequa Partnership: Enterprise-Grade Cognitive Search at Scale
Delivering cognitive search at the scale AstraZeneca required is not just a technology challenge — it is an organizational and change management one. The Accenture–Sinequa partnership brings together Sinequa’s AI-powered search platform with Accenture’s enterprise transformation expertise, providing organizations with both the technology and the implementation capability needed to move from pilot to production at global scale.
Together, Accenture and Sinequa have helped leading organizations across life sciences, energy, manufacturing, and financial services build connected knowledge platforms that reduce time-to-insight, improve decision quality, and create lasting competitive advantage from the enterprise data they already have.
Key Takeaways from This Webinar
- Why limiting search to intranet navigation leaves the majority of enterprise knowledge value untapped
- How AstraZeneca approached the journey from basic search to enterprise-wide cognitive intelligence — including the organizational and architectural steps that made it scalable
- What it means to treat cognitive search as a strategic platform rather than a point solution
- How AI-powered search analytics creates a continuous feedback loop that improves knowledge access over time
- The practical role of a systems integrator like Accenture in accelerating deployment and driving adoption across a global workforce
Watch the video
Frequently Asked Questions
Cognitive search is an AI-powered approach to enterprise information retrieval that goes beyond keyword matching. It uses natural language processing, machine learning, and knowledge graph technology to understand the meaning and context of a query — returning relevant results from across multiple data sources, formats, and languages, even when the user doesn’t know the exact terminology. Traditional enterprise search relies on keyword indexing and typically fails at scale, in multilingual environments, or when querying unstructured content like documents, emails, and reports.
AstraZeneca worked with Sinequa and Accenture to build a cognitive search platform capable of serving a global workforce across R&D, commercial, and operational functions. The implementation moved from initial pilot — proving the value of connected, AI-powered search within a specific business unit — to enterprise-wide deployment, integrating dozens of internal and external data sources into a unified, searchable knowledge layer accessible to employees worldwide.
Accenture’s Content Analytics Group provided enterprise transformation expertise alongside Sinequa’s technology — covering information architecture design, taxonomy development, change management, and deployment strategy. For an organization of AstraZeneca’s scale and complexity, the combination of best-in-class search technology and experienced systems integration was critical to achieving production-grade deployment.
Enterprises that deploy cognitive search platforms typically see significant reductions in time spent searching for information (often 35–40%), faster onboarding for new employees, reduced duplication of research effort, improved quality of decisions through better access to internal expertise and competitive intelligence, and stronger compliance posture through more consistent access to regulatory and policy documentation.
Life sciences organizations deal with exceptionally high volumes of complex, heterogeneous data — scientific publications, clinical trial records, regulatory filings, patent databases, compound data, and proprietary R&D documentation. Cognitive search platforms that understand biomedical terminology, support multilingual queries, and connect internal and external sources simultaneously deliver outsized value compared to traditional search in this context.
Cognitive search and Retrieval-Augmented Generation (RAG) are complementary, not competing, technologies. Cognitive search is the retrieval layer — finding and ranking the most relevant documents and passages across an enterprise’s data sources. RAG uses that retrieved content to ground the responses of a large language model (LLM), ensuring AI-generated answers are accurate, sourced, and traceable. Sinequa’s platform supports both, making it the foundation for both search-first and AI assistant-first deployments.
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