Our natural language processing system is focused on extracting and converting unstructured textual information into measurable metrics. The system features:
Our platform utilizes algorithmic models where humans apply mind, experience, sense, discernment, and knowledge. We’ve built a proprietary approach to NLP that allows us to identify the entities, their roles, concepts, and relationships among texts of any nature.
Indexica’s virtual common-sense system was built by our experts from the fields of linguistics, psychology, and artificial intelligence. Self-engineered algorithms, real-world rules, advanced word classification systems, word disambiguation processes, contextual part-of-speech tagging, and statistical learning are at the core of our system.
Constantly learning from text ingestion, Indexica produces exclusive insights from textual data by combining new knowledge with extracted metrics. With this recursive approach, extracted knowledge is continually evolving while benefiting from self-generated inferred connections.
We take velocity seriously in order provide intelligence at a faster pace than non-optimized systems and the traditional news cycle would typically permit.