As powerful as semantic search has become it is still missing the human ability to identify new connections or discover different avenues to investigate. This new technology allows this to happen in a structured and evidential way to deliver new insights to organisations that seek to gain more value from their structured ontologies and knowledge graphs.
This new tool works as we would in testing, trying and re-tuning our search strategy to reveal new connections and relationships.
This is where this tool starts to bridge the gap between the traditional human approach and modern machine learning. Effectively, it is a semi-automated method of taking a human approach to traditional semantic queries.
Designed for deriving new business intelligence, it allows organisations to discover hidden insights from previously hidden but closely related information relevant to the search (e.g. what else?, who else?).
New Insights — Changes to divergence (the importance of search parameters) combined with human preferences allow users to explore alternative avenues and derive new insights
|.||Fast — a semi-automated approach allows organisations to quickly derive more value from their data and is ideal for revealing fuzzy matches at scale.|
|.||Evidential — modern machine learning techniques can be a black box and very difficult to justify or explain. This tool produces evidenced recommendations that can be interrogated and justified.|
- Defence & Security – Intelligence analysis and policing
- Insurance – Fraud detection
- Financial – Money laundering
- Retail – Customer insights engine
GB Application: GB2000969.2
Sole Rights / Non-exclusive
Available to license