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Discover Context to Unlock Superior Data
Connect missed customers via Darkmath's consumer data enriched high-dimensional vector space
AI that actually delivers value. See the colorful nuance for superior Id resolution and audience creation.
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Not Just Better, But Novel
DarkMath takes a new approach to entity resolution, custom look-alike audiences and fraud detection. Find connections and contextual profiles currently missed. With DarkMath you are not just enriching your data, you are discovering a new dimension.
Easy Integration
Seamlessly upload encrypted data or shared tables returning measurable increases in record reach, precision and audience performance.
Custom Embedding
A mountain of consumer records and unique data taylored to state of the art LLM models deliver a unique dimensionality. Learning Neural networks insure continuous improvement.
Innovation
Proprietary Algorithms practically applied from quantum physics deliver game-changing superior similarity identification, campaign performance and anomaly detection.
Experimental Sandbox
Access our vector database for testing and developing innovative solutions.
DarkMath doesn't just match text, it understands it.
Our technology comprehends context, location, and meaning. By embedding semantic understanding into our vector database, we can distinguish nuances that other systems miss, whether it's different Eiffel Towers or similar-looking customer records that represent distinct individuals.
Differentiate between people with identical names in different locations
Recognize when similar company names represent different businesses
Understand when variations in addresses refer to the same property
Connect customer records across channels even with partial information
About DarkMath
DarkMath is revolutionizing how businesses connect disparate data to uncover new vectorized representations and nuance through our groundbreaking proprietary technology. We combine advanced AI, including Large Language Models and deep learning, with sophisticated data embedding techniques to solve complex data integration challenges and context at unprecedented scale and accuracy.
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