NLP & Machine Learning Optimized for Financial Services Using Proprietary Data
Proprietary algorithms designed to determine relevance, novelty, similarity, ‘trendingness’, and precise data extraction from text.
Proprietary network of entities, identifiers, synonyms, co-occurrence frequencies, and word embedding vectors modeled to support NLP.
Multi-factored model designed to automatically surface novel and important intelligence specific to a user’s interests and workflow.
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