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Omnisient - Collaborative Consumer Intelligence
Omnisient is a privacy-preserving data collaboration company that lets banks, insurers, retailers and consumer brands analyze their first-party data together without ever sharing or exposing it. Using privacy enhancing technologies, US-patented Crypto-IDs and AI-powered data clean rooms, the platform matches mutual customers across datasets so lenders can score credit-invisible and thin-file consumers using alternative behavioral data - all while personal information never leaves the owner's environment. Founded in Cape Town and now expanding into the United States, the company protects hundreds of millions of consumer records for more than 100 enterprises.
Provable Markets
Provable Markets is a New York-based financial technology company modernizing the securities lending and securities finance markets. Through Aurora, its SEC-registered, vertically integrated Alternative Trading System, it combines encrypted real-time order matching, automated post-trade lifecycle management, and connectivity to central clearing (NSCC CCP) and settlement (DTC) infrastructure. Founded in 2020 by CEO Matthew Cohen and rooted in cryptographic research on secure multi-party computation, the company aims to replace the instant-message-and-spreadsheet workflows of a roughly trillion-dollar market with cloud-native, low-latency, transparent trading.
Jon Jacobson
Jon Jacobson is the co-founder, Group CEO and CTO of Omnisient, a privacy-preserving data collaboration platform that lets banks, insurers, retailers and healthcare organizations share and analyze consumer data without exposing raw personal information. A software engineer with more than 25 years building data platforms, he founded Omnisient in South Africa in 2019 to attack a specific problem: nearly two billion people are shut out of affordable financial services because they lack the behavioral data lenders use to assess risk. His platform uses cryptography to tokenize and match datasets locally, turning loyalty-card and retail data into alternative credit signals.