The Hypothesis Engine autonomously analyzes data to generate insights and composite features, discover patterns, or hook datasets together.
Row-level information can be hidden from certain datasets, while still providing view-only access to the data schema.
Work with raw, granular data as AI platforms sit between data sources and users, surfacing patterns from merged, “unseen” data sets.
Existing solutions for analyzing sensitive data either compromise privacy for signal or signal for privacy.
Anonymization and encryption have proven to be far less secure than originally envisioned, while aggregation and data synthesis sacrifice too much data granularity.
SparkBeyond leverages Blindfolded analytics to unlock deep value from data without sacrificing security or privacy.
A partnership renewal between global CPG and EPOS data vendor was made possible by facilitating analytics on daily-level category & brand sales data.
Global financial institution targeted “un-lendable applicants” by leveraging previously-siloed internal and external datasets to increase nuance in risk scoring.
Leveraged HMO's extensive patient data set to identify patients at risk for colon cancer. Results could then monetized by HMO as a physician alert system.
A partnership renewal between global CPG and EPOS data vendor was made possible by facilitating analytics on daily-level category & brand sales data.
Global financial institution targeted “un-lendable applicants” by leveraging previously-siloed internal and external datasets to increase nuance in risk scoring.
Leveraged HMO's extensive patient data set to identify patients at risk for colon cancer. Results could then monetized by HMO as a physician alert system.
How to maximize conversions with hyper-personalized customer experiences.