Duality Labs is a technology company specializing in privacy-enhancing technologies (PETs) that enable secure data collaboration across various industries. Founded by leading cryptographers and data scientists, the company focuses on facilitating secure analysis and artificial intelligence (AI) operations on encrypted data, ensuring compliance with data privacy regulations and protection of intellectual property. Duality Labs serves sectors such as financial services, healthcare, and government, providing solutions that allow organizations to extract value from sensitive data without compromising privacy.
Key Strategic Focus
Duality Labs' strategic objectives center on operationalizing PETs to enable secure data collaborations within business ecosystems, including customers, suppliers, and partners. The company's core technologies include fully homomorphic encryption, federated learning, and trusted execution environments, which collectively support privacy-preserving data analysis and AI model training. By leveraging these technologies, Duality Labs targets markets that require stringent data privacy compliance, such as financial services, healthcare, and government sectors.
Financials and Funding
Since its inception, Duality Labs has secured a total of $56 million in funding over four rounds. The most recent funding round was a Series B, raising $30 million on July 27, 2021. Notable investors include Euclidean Capital, LG Technology Ventures, National Bank Private Investment, NAVentures, and Plug and Play Tech Center. The capital raised is intended to enhance the company's technological capabilities, expand its market reach, and further develop its suite of privacy-preserving data collaboration solutions.
Technological Platform and Innovation
Duality Labs distinguishes itself through its proprietary SecurePlus platform, which enables secure analysis and AI operations on encrypted data. This platform incorporates several advanced PETs:
- Fully Homomorphic Encryption (FHE): Allows computations to be performed directly on encrypted data without the need for decryption, ensuring data remains confidential throughout the analysis process.
- Federated Learning: Enables AI models to be trained across decentralized data sources without sharing raw data, preserving privacy while leveraging diverse datasets.
- Trusted Execution Environments (TEE): Provides secure enclaves for data processing, protecting sensitive information from unauthorized access during computation.
These technologies collectively empower organizations to collaborate on sensitive data securely, unlocking insights while maintaining compliance with data protection regulations.
Leadership Team
Duality Labs is led by a team of experts with extensive experience in cryptography, data science, and business development:
- Dr. Alon Kaufman, Co-founder and CEO: With over 15 years in the high-tech sector, Dr. Kaufman has a background in commercializing data science technologies and leading industrial research and corporate innovation teams. Prior to founding Duality, he served as RSA’s Global Director of Data Science & Innovation.
- Ms. Rina Shainski, Co-founder and Chairwoman: Before co-founding Duality, Ms. Shainski was a general partner at Carmel Ventures (now Viola VC), leading investments and serving on the boards of various high-tech companies in areas such as mobility, cybersecurity, and digital media.
- Prof. Shafi Goldwasser, Co-founder and Chief Scientist: A renowned cryptographer, Prof. Goldwasser is the inventor of several foundational cryptographic technologies, including probabilistic encryption and multi-party secure protocols. She was awarded the ACM Turing Award in 2012 for her transformative work in the field.
- Prof. Vinod Vaikuntanathan, Co-founder and Chief Cryptographer: An associate professor at MIT, Prof. Vaikuntanathan is a co-inventor of modern fully homomorphic encryption systems and various lattice-based cryptographic primitives.
- Dr. Kurt Rohloff, Co-founder and CTO: Dr. Rohloff is a co-founder of the PALISADE open-source homomorphic encryption software library and has led defense industry consortia developing leading open-source libraries. He is also a co-founder and steering committee member of the HomomorphicEncryption.org industry consortium.
Competitor Profile
The market for privacy-enhancing technologies is competitive, with several key players:
- Cape Privacy: Founded in 2018 and headquartered in New York, Cape Privacy offers a platform for secure collaborative data science, enabling teams to run machine learning models on encrypted data without exposing it.
- Enveil: Established in 2016 in Fulton, Maryland, Enveil provides a ZeroReveal solution that allows organizations to perform secure data searches, analytics, and sharing without revealing the content or results.
- Inpher: Based in New York and founded in 2015, Inpher specializes in secret computing, enabling privacy-preserving machine learning and analytics across distributed data sources.
These competitors focus on similar areas of secure data collaboration and privacy-preserving analytics, each bringing unique approaches and technologies to the market.
Strategic Collaborations and Partnerships
Duality Labs has established significant partnerships to enhance its market position and innovation capacity:
- DARPA: Collaborated on projects to advance secure data analysis capabilities for defense applications.
- Intel: Partnered to integrate privacy-preserving technologies into Intel's data processing solutions.
- Scotiabank: Worked together to implement secure data collaboration tools within the financial services sector.
- Oracle and IBM: Engaged in partnerships to develop and deploy secure data analysis platforms for enterprise clients.
- World Economic Forum (WEF): Participated in initiatives to promote data privacy and security standards globally.
Operational Insights
In the competitive landscape of privacy-enhancing technologies, Duality Labs differentiates itself through its comprehensive suite of PETs, including fully homomorphic encryption and federated learning. The company's focus on enabling secure data collaboration.
