Duality Query is a privacy-enhancing query platform that enables confidential, quantum-secure queries across siloed, cross-domain, and multimodal datasets without revealing the query content or exposing the underlying data. The platform uses Privacy Enhancing Technologies (PETs) including Fully Homomorphic Encryption (FHE), Federated Learning, and Trusted Execution Environments to allow encrypted computation across distributed data sources. It is built on OpenFHE, an open-source homomorphic encryption library. Key capabilities include: - Zero Footprint querying: queries run on encrypted data at each data owner's location without moving or replicating datasets - Multimodal data support: handles structured and unstructured data including text, images, and logs under a unified privacy-preserving framework - Cross-domain collaboration: supports queries spanning multiple organizations, networks, jurisdictions, or departments, with each party retaining control over what is revealed - Built-in data harmonization: aligns schemas and formats across multiple data owners within a single secure platform - Secure aggregation: aggregates encrypted results from multiple data owners while preserving privacy - Governance controls: data owners can define who accesses data, which computations are permitted, and at what frequency Target use cases include financial crime investigations (KYC, AML, fraud detection), intelligence community operations, healthcare data collaboration, government agency data sharing, and secure data monetization by data brokers and service providers.