Top 50 Differential Privacy

Oblivious provides a data privacy platform that utilizes differential privacy and secure enclaves to enable organizations to analyze sensitive data without exposing individual information to unauthorized users, including internal data scientists. This technology minimizes data exposure risks while allowing seamless integration with existing systems, facilitating secure collaboration with internal and external partners.

The startup develops data privacy software that enables organizations to find, redact, and generate synthetic personally identifiable information while integrating seamlessly into existing infrastructures. This allows businesses to analyze large datasets containing sensitive information without compromising user privacy.

PVML is a data access platform that utilizes differential privacy to enable secure, real-time analytics on sensitive datasets without exposing personally identifiable information. This technology allows organizations to maintain compliance with privacy regulations while facilitating safe data sharing and collaboration across teams and third parties.

Oasis Labs provides a privacy-first cloud computing platform built on blockchain technology, enabling organizations to utilize data securely while maintaining confidentiality. Their enterprise solutions leverage decentralized architecture to protect sensitive information, facilitating responsible data use in compliance with privacy regulations.

The startup provides a privacy-driven ecosystem that utilizes advanced cryptographic techniques to protect user identities and transactions on blockchain networks. This solution addresses the risks of data exposure and unauthorized access, ensuring users maintain control over their digital presence.

Duality provides a platform that utilizes privacy-enhancing technologies to enable secure collaboration and analysis of encrypted data across organizations. This approach addresses challenges related to data privacy, intellectual property protection, and regulatory compliance, allowing enterprises to derive insights without exposing sensitive information.

The startup offers a data security platform that classifies both structured and unstructured data, identifying personal and sensitive information to ensure compliance with regulations like GDPR and CCPA. By providing a real-time catalog of data assets and customizable detection rules, organizations can effectively manage their data security and privacy posture.

Provides a data clean room platform that enables businesses to securely collaborate and analyze decentralized data without moving it, preserving privacy and compliance. This technology allows organizations to derive actionable insights from walled gardens and private datasets, supporting use cases like advanced segmentation, measurement, and model enrichment without requiring coding expertise.

The startup offers a data infrastructure platform that enables secure collaboration among multiple parties while maintaining data ownership and privacy. Its technology features smart access rights management and customized integrations, allowing clients to share and compute data without the risk of privacy leakage.

Streamdal provides a data performance monitoring tool that embeds privacy controls within application code to detect and manage personally identifiable information (PII) in real-time. This solution prevents unintended exposure of sensitive data across messaging systems and data pipelines, ensuring data integrity and compliance.

PrivaSapien develops a Privacy Enhancing and Responsible AI (PERAI) platform that utilizes patented technologies like Privacy X-Ray and Event Horizon to visualize privacy risks and ensure GDPR compliance through advanced data anonymization. The platform addresses the critical issue of data misuse by providing enterprises with tools to manage privacy risks effectively while maintaining data utility for collaboration and value creation.

The startup develops a privacy-enhancing technology platform that employs federated learning to enable secure data collaboration among organizations. This approach allows clients to share valuable insights without exposing sensitive information, thereby strengthening their defenses against cybercrime.

The startup offers a data ecosystem platform that utilizes hardware cryptography and machine learning to enable secure data access and analysis for data scientists and business users. This technology allows organizations to collaborate on sensitive data without compromising confidentiality, unlocking valuable insights that would otherwise remain untapped.

The startup provides privacy-guaranteed synthetic data generated through advanced algorithms for training AI models. This approach mitigates the risks associated with using real data, ensuring compliance with data protection regulations while enhancing model accuracy and performance.

Pyte provides a secure multiparty computation platform that enables enterprises to collaborate and perform computations on encrypted data without ever decrypting it, ensuring privacy compliance and protection against data breaches. This technology allows organizations to leverage sensitive data across cloud environments and partners while maintaining confidentiality, eliminating the need to share personally identifiable information.

Roseman Labs provides a platform for decentralized data analytics using Multi-Party Computation, allowing organizations to securely link and analyze sensitive datasets without exposing raw data. This technology enables compliance with GDPR while facilitating data-driven insights across healthcare and public sectors, enhancing decision-making and operational efficiency.

The startup offers a data security platform that enables clients to securely analyze and collaborate on data assets without exposing sensitive content. By utilizing advanced techniques for data anonymization and secure insights derivation, the platform facilitates safe data monetization and cross-matching of third-party data.

Opaque provides a confidential computing platform that enables organizations to analyze encrypted data in the cloud without compromising privacy. By leveraging cryptographic techniques, Opaque allows businesses to unlock sensitive data for AI workloads while ensuring compliance with data protection regulations.

Tune Insight provides an Encrypted Computing solution that utilizes federated learning and homomorphic encryption to enable secure data collaborations without transferring sensitive information outside an organization. This technology allows businesses to perform collective analytics and machine learning on encrypted data, minimizing data liability and ensuring compliance with privacy regulations.

The startup offers a privacy and compliance software platform that audits personal data flows and generates process documentation to ensure adherence to regulations. By processing and documenting data breaches, the platform enables industries such as healthcare and finance to manage data transparently while focusing on their core business operations.

The startup develops multi-party computation technology that enables secure and decentralized joint computation of functions while keeping individual inputs private. This platform enhances digital asset security for businesses in the crypto space by maintaining computational complexity and scalability.

Maya Data provides a data anonymization solution, AppSafe, that transforms sensitive customer and business data into GDPR-compliant datasets for AI and machine learning model training. This technology enables organizations to utilize production data without compromising privacy or requiring access to the production environment, resulting in a 70% cost reduction and 80% faster implementation compared to traditional methods.

Subsalt provides a query engine that automates the anonymization of regulated enterprise data, ensuring compliance with data protection laws without lengthy legal processes. By generating high-quality synthetic data that preserves row-level granularity, Subsalt enables organizations to share sensitive information quickly and securely with internal teams and partners.

Provides Confidential AI models that use homomorphic encryption and secure enclaves to process data in an encrypted state, ensuring that no unauthorized party, including the service provider, can access sensitive information. This approach eliminates data leaks during AI training and inference, enabling secure development of tools like code copilots, semantic search, and personalized assistants without compromising privacy.

TripleBlind develops quantum-safe and cryptographically secure software solutions, including Privacy Suite for HIPAA-compliant sharing of protected health data and SecuriKey to prevent account takeover attacks. These products enable secure data sharing and enhance user account protection, addressing critical privacy and security challenges in the digital landscape.

Privado automates privacy code scanning to provide real-time visibility and governance over how personal data is collected, used, shared, and stored within software applications. This technology enables organizations to quickly identify privacy risks and ensure compliance with regulations like GDPR and CPRA, reducing the time to build data maps from months to days.

The startup offers an encrypted learning platform that enables organizations to collaboratively develop machine learning models while protecting proprietary and confidential data. By facilitating secure data sharing with external parties, the platform enhances data models and increases business value without compromising privacy.

Provides a privacy-preserving analytics and AI platform that enables data scientists and analysts to query sensitive data without direct access, using differential privacy, synthetic data generation, and privacy-first query rewriting. This approach ensures compliance with data protection regulations, prevents breaches, and allows organizations to unlock the full value of their data while maintaining security and privacy.

The startup offers a privacy management platform that utilizes automated incident detection and remediation to enhance data privacy practices for engineering and security teams. By providing actionable intelligence on personal data usage, the platform mitigates financial and reputational risks associated with data privacy incidents.

The startup offers a data insights platform that utilizes advanced encryption techniques to analyze sensitive data without exposing its contents. This enables businesses to enhance their products and services while ensuring compliance with privacy regulations and maintaining user data sovereignty.

Privacy Dynamics provides a data anonymization platform that enables development and testing teams to utilize production data without exposing sensitive customer information. This solution mitigates the risks associated with data breaches and compliance violations in regulated industries by ensuring that raw data is transformed into anonymized datasets suitable for analytics and development environments.

The startup provides a platform that utilizes generative AI while ensuring data privacy through advanced encryption techniques. This approach allows businesses to leverage AI capabilities without compromising sensitive information, addressing concerns over data control and security.

Anonym develops privacy-preserving machine learning technologies that enable advertising platforms to optimize performance without sharing personally identifiable information. By utilizing confidential computing environments, Anonym enhances audience targeting and measurement while safeguarding user privacy, addressing the challenges of data sharing in the digital advertising industry.

Datavillage provides a platform for secure data collaboration that enables businesses to analyze sensitive information without sharing raw data, ensuring compliance with privacy regulations. This technology addresses challenges in training AI models by allowing organizations to leverage confidential data for improved insights and fraud detection.

The startup offers a commercial open-source platform that provides a suite of security and privacy APIs for developers, enabling them to build compliant cloud applications efficiently. By integrating these security building blocks, engineering teams can accelerate their development process while maintaining a robust security posture.

The startup offers a privacy protection platform that utilizes an AI-driven assessment engine to continuously monitor and evaluate privacy risks for businesses. This technology enables organizations to efficiently manage privacy compliance and implement targeted risk mitigation strategies based on their specific resource availability and operational maturity.

The startup operates a data privacy platform that integrates privacy-enhancing technologies with built-in governance and controls to ensure compliance with data protection regulations. By automating the application of data policies, the platform significantly reduces the time and costs associated with managing sensitive data for businesses.

Acompany provides privacy protection solutions through secure computing technologies, including Confidential Computing and Secure Aggregation, to enable safe data collaboration and governance. The startup addresses the complexities of digital privacy by helping businesses maximize data utilization while minimizing privacy risks.

DRIC develops a data privacy and storage platform that utilizes encryption and secure access controls to protect sensitive information. The platform addresses the challenges of data breaches and compliance with privacy regulations by ensuring that user data remains confidential and securely stored.

The startup develops data security software that enables enterprises to securely publish and share sensitive digital assets while maintaining compliance with data protection regulations. This technology allows organizations to leverage valuable data for business insights and analytics, unlocking new revenue opportunities without compromising data integrity.

The startup develops homomorphic encryption software that secures data-in-use, data-at-rest, and data-in-transit across any cloud environment. This technology enables businesses to protect sensitive information throughout its entire lifecycle without compromising usability.

The startup offers a crypto-platform that utilizes full encryption, consensus algorithms, and code-is-law smart contracts to ensure data integrity and confidentiality during processing. This technology enables clients to deploy confidential computing applications securely on both a private platform and a public network, protecting data at rest, in transit, and in use.

Inpher, Inc. provides privacy-preserving machine learning solutions using technologies such as Secure Multiparty Computation and Fully Homomorphic Encryption, allowing organizations to analyze sensitive data without transferring it. Their SecurAI platform enables secure and compliant use of generative AI, ensuring that proprietary data remains private while enhancing predictive model accuracy.

Xafe offers a cognitive data privacy platform that secures sensitive data sharing and analysis using differential privacy. It manages privacy budgets and injects calibrated noise into query results, protecting individual data while maintaining statistical utility for compliance and insights.

Linksight operates a platform that utilizes secure multiparty computation, secret sharing, and fully homomorphic encryption to enable privacy-preserving data collaborations among multiple parties. This technology allows organizations to perform joint analyses on combined datasets without exposing sensitive information, facilitating data-driven decision-making while maintaining compliance with privacy regulations.

Soda Labs utilizes garbled circuits and multi-party computation (MPC) to provide end-to-end encryption for data transactions in web3 environments, ensuring that sensitive information remains confidential and secure. The platform addresses the lack of privacy in digital asset management by enabling organizations to analyze and derive insights from their data without exposing it to unauthorized access.

Algemetric provides secure multiparty computation technologies that enable privacy-preserving collaboration on sensitive data. This approach ensures that organizations can analyze and share data without compromising confidentiality or security.

BaseBit provides a privacy computing platform that enables secure data sharing and collaboration across industries, utilizing full-stack technologies and advanced AI algorithms. This approach addresses the challenge of data privacy and security while facilitating the integration and interoperability of diverse data sources for enhanced analytics and decision-making.

The startup offers a business development platform that utilizes machine learning algorithms to automatically identify and redact private or sensitive information from documents. This technology minimizes the need for human intervention in the removal of consumer identities, trade secrets, and intellectual property, ensuring compliance and data security when sharing datasets with third parties.

OCTOPIZE develops data analytics software that utilizes advanced anonymization techniques to protect sensitive information while providing intuitive data visualization. This solution enables organizations to analyze and share data without compromising privacy, facilitating compliance with data protection regulations.