The challenge is to get information into the hands of knowledge workers. The data-driven enterprise typically does this by relying on the effort of those workers. This imposes a cognitive burden, which refers to the extra thought and effort that we humans require to evaluate the available options and make optimal decisions.
Sinequa provides a search and insight platform to reduce this burden, incorporating the depth of over 25 years of linguistics research as well as the latest text analytics technology, including that of semantic software solutions provider SciBite. These layers of analysis are applied to extract meaning from unstructured text and are then brought together to provide the most relevant and accurate results.
The partnership between Sinequa and SciBite allows the application of relevant semantic enrichment over a life science company’s entire document collection as well as public data such as PubMed, patents, grant applications, and so on.
During this webinar we will be demonstrating the combination in action over a corpus of 25 million documents.
We partner with leading enterprise search platforms to enhance real-time big data analytics for pharma and biotech companies. Semantic search capabilities improve the accuracy of search results allowing companies to make data-informed decisions. Find out more about how SciBite’s solutions can help unlock the potential of the R&D data in your business.
Sam leads partnerships and alliances at SciBite, working collaboratively with existing partners and developing new partnerships aligned to SciBite’s strategic goals. He has a strong technical background in the life sciences, with a PhD in Protein Biochemistry from the University of Nottingham and post-doctoral training in bioinformatics within the department of Neurosurgery at the University of California San Francisco.
Prior to Joining SciBite he held technical sales and commercial roles at Carl Zeiss and most recently led business development at Repositive, building relationships with contract research organisations, biotech’s and pharma companies, facilitating data exchange and search across multiomic datasets. He has a good grasp of the challenges of dealing with unstructured scientific data, and collaboratively developing practical solutions to overcome these.