Quickness in SciFinder

Relevance engine

SciFinder is the most advanced chemistry relevance engine in the industry helping your team’s efficiency by thinking like your researchers. Relevance engines like SciFinder are advanced search engines that improve the meaningfulness of each search. Using algorithms, the engine is built to take into account specific parameters and context of a search to produce more precise results. 

Imagine the impact on R&D productivity if researchers were able to redirect back into the laboratory half a day per week they spend finding information to advance discovery?

SciFinder’s relevance engine helps your team’s quickness because it is pointed and narrows searches so the researcher doesn’t have to sift. This will improve their rate of research and performance so you can report faster on findings. 
Reliable answers are accessible from validated sources and have the latest research. SciFinder’s relevance engine will help cut through increasing workload with more efficiency because it understands the researcher’s needs. 

Philippe Y. Ayala explores how relevance engines can alleviate the issue when, “research progress can be compromised if key papers and scientific data cannot be found quickly.”

Philippe Y. Ayala

Machine learning

SciFinder leverages the power of Machine Learning to gain and maintain a competitive edge for your organization. Machine Learning within SciFinder accelerates innovation and growth while improving efficiency and reducing costs.   

SciFinder is the platform that uses predictive tools that leverage Machine Learning algorithms and big data, so that scientists can increase their quickness by narrowing down specific chemicals and conditions far faster and more accurately than manual efforts. 

Even the most seasoned chemists can only make predictions based on their own experiences and the data they have available.