Semantic AI analyses the meaning behind words to improve search and information findability. It enables machines to interpret the intent behind ambiguous terms. For example, ‘Glasgow bus timetables’ and ‘Departure/arrival times Glasgow buses” both mean the same thing – but a computer may not recognize this and provide the user with two very different sets of results. Another example could be searching for "rock music". Without semantic AI, a computer might interpret "rock" to mean a stone, instead of a music genre.
Semantic AI simulates a human-like understanding of online search terms, giving people more accurate results faster. Because content is intrinsically linked to the implicit, hidden, or intangible meaning behind a user’s search terms, the search results produced are much better aligned with what the user was actually looking for.
- Autocomplete searches
- Enable chatbots and voice assistants
- Instant taxonomy tagging for automatic classification
- Deliver personalized results and recommendations
- More efficient and effective findability of information
- More relevant search results
- Better customer experiences
- Greater employee productivity
- Improved decision making