Cognitive Search for Research & Development.
R&D is the epicenter of an organization, whether within a large aircraft manufacturer or a leading automobile company looking to develop cutting edge products and services or a pharmaceutical company accelerating time-to-market for new drugs or a CPG company reinventing waning products.
R&D thrives on information: customer information, expert information, product information, scientific information, market information, and competitive information. To be at the forefront of innovation, R&D departments need complete visibility into both new and historical information across the entire enterprise as well as access to research from external public and premium information services. This is no easy feat in today’s world where we are inundated with data — more data, more opportunities and more challenges. As a result, many companies depend on Cognitive Search & Analytics (CS&A) solutions to:
- Accelerate delivery of innovative products to market.
- Optimize and manage available resources and knowledge while leveraging intellectual property.
- Devise methods to reduce product development costs and eliminate re-work.
- Improve product compliance both internally and externally.
- Understand consumer and market demands and improve responsiveness.
- Resolve product issues quickly and efficiently to gain and keep customer trust.
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Other whitepapers.
KM World: Cognitive Search Brings the Power of AI to Enterprise Search
What is Cognitive Search? Forrester, one of the leading analyst firms, defines Cognitive Search in a recent report as: The new generation of enterprise search that employs AI technologies such as natural language processing and machine learning to ingest, understand, organize, and query digital content from multiple data sources. Here is a shorter version, easy to memorize: Cognitive Search = Search + NLP + AI/ML.
KM World: Best Practices in Cognitive Computing
This white paper offers a definition of Cognitive Computing supported by concrete use cases showing how cognitive information systems are capable of extracting insights from big and diverse data sets for users in their work context.
KM World – Best Practices for Intelligent Search
This white paper will explore some of the best practices for becoming information-driven using intelligent search by leveraging the experience Sinequa has gained working with large customers within knowledge-intensive industries.
