Semantic Search for the Enterprise:
Get fewer, more relevant results with semantic search for the enterprise
Having the right information at your fingertips is critical, whether you’re a computational biologist evaluating relevant proteins to identify a promising drug target, a customer service representative troubleshooting a problem, or a manufacturing executive looking for the most readily available replacement part. In each scenario, the information required to solve these problems is spread across different systems and lives in a variety of formats.
As a result, people wind up manually hunting down information across various systems — wasting significant time — or making critical errors because their decisions were not properly informed.
While there are plenty of enterprise search options on the market, they’re failing in the face of increasing complexity and performance demands.
Read our whitepaper to find out:
- Why Springer Nature and others choose semantic search in order to increase productivity
- How semantic search is able to deliver fewer, more relevant results in order to cut down on time spent searching by up to 90%
- What distinguishes Stardog's semantic search from popular search tools like Elasticsearch
- How semantic search addresses increasing user demands, including supporting AIs like chatbots and voice search applications