About SecurePlus
SecurePlus is a secure data collaboration software from Duality Technologies that protects data privacy and security for collaboration among multiple data owners and analyzing parties. It combines Secure Query, Secure Collaborative AI, and Duality Assistant Agent so users can effectively analyze sensitive data while maintaining strict privacy standards. The platform also supports Secure Federated Analytics and is open source to foster community collaboration and transparency. SecurePlus enables organizations to access valuable insights from sensitive datasets without compromising individual privacy. Key capabilities: Secure Query Secure Collaborative AI Duality Assistant Agent Secure Federated Analytics Open Source Best for: organizations that need secure data collaboration and privacy-preserving analytics.
The Duality Platform by Duality Technologies represents a transformative advancement in secure data collaboration, uniquely positioned to meet the stringent demands of organizations handling sensitive or regulated information. At its core, the platform empowers enterprises to analyze and share data insights without ever exposing the raw data itself. This capability is made possible through the integration of advanced Privacy Enhancing Technologies (PETs) such as Fully Homomorphic Encryption (FHE), Differential Privacy (DP), Multi-Party Computation (MPC), and Trusted Execution Environments (TEE), all operationalized in a user-friendly environment that requires no deep cryptographic expertise. By removing the traditional barriers associated with privacy-compliant collaboration, Duality enables real-time analytics, machine learning, and data sharing between trusted and semi-trusted parties, ensuring compliance with regulations like GDPR, PDPA, and HIPAA while retaining the business value of data. One of the most significant innovations is the Duality Assistant, which introduces a conversational, chat-based user interface to simplify complex tasks. This natural language interaction makes data querying and AI model generation accessible even to users without a technical background, greatly expanding usability across organizational roles.
Pros & Cons
- Advanced privacy technologies: Uses Homomorphic Encryption, Federated Learning, MPC, and more to protect sensitive data
- Encrypted data analysis: Enables SQL-like queries, machine learning, and analytics without exposing raw data
- Flexible collaboration: Supports cross-border, multi-party data sharing with granular access controls
- Enterprise-grade scalability: Handles large datasets and integrates with existing infrastructure via SDKs and APIs
- End-to-end lifecycle support: Covers ingestion, schema alignment, transformation, and analysis in one platform
- Compliance by default: Built to meet stringent data privacy regulations across industries
- Trusted by major organizations: Partners include AWS, Intel, Oracle, IBM, and DARPA
- Complex setup: May require technical expertise to configure cryptographic workflows and integrations
- Performance trade-offs: Encrypted computations can be slower than traditional methods depending on use case
- Limited public adoption: Still emerging in mainstream enterprise environments compared to legacy platforms
- Specialized use cases: Best suited for regulated industries like healthcare, finance, and government
Features
Key features
Enables secure machine learning, analytics, and queries on encrypted data using multiple Privacy Enhancing Technologies (PETs).
Allows users to set different access levels and data-sharing permissions for various partners within a project.
Facilitates open and secure data flows across different borders and domains.
Provides tools for schema alignment, data transformation, feature engineering, normalization, and fuzzy matching in a secured environment.
Utilizes advanced cryptography and data science to deliver quick insights on real-world data.
Easily integrates with existing data assets, cloud storage, software infrastructure, and workflows using SDK and APIs.
Additional features
Allows for more secure and efficient open data flows.
Protects data privacy while enabling collaboration.
Provides intelligent, privacy-preserving AI partners to guide research, extract insights, and generate reports securely.
Runs high-performance SQL-like encrypted queries for privacy-preserving insights.
Executes any model on any data within a Trusted Execution Environment (TEE) while protecting assets.
Facilitates secure federated learning and analytics collaboration on dispatched data located anywhere.
Leverages advanced cryptographic techniques to enhance Privacy Enhancing Technologies (PETs).
Performs privacy-preserving queries on decentralized data sets.
Utilizes leading open-source FHE to enable computation on encrypted data without decryption.
Empowers multiple parties to collaborate and gain insights while keeping sensitive data protected.
Seamlessly integrates with existing systems for quick and scalable project setup.
Supports secure model training and inference on encrypted data or models.
Allows execution of descriptive statistics on encrypted data.
Enables running SQL-like queries on encrypted data.
Provides granular access levels and data-sharing permissions for collaboration partners.
Built-in controls to reduce the risk of data leakage.
Ensures data practices adhere to stringent data privacy regulations.
Includes schema alignment, data transformation, feature engineering, normalization, and fuzzy matching.
Ensures first-party data and sensitive information are protected with built-in tools.
Tools for preparing data for secure multi-party collaboration.
Helps organizations meet evolving privacy compliance needs.
Offers easy setup for collaboration networks with full control and governance over data and models.
Harnesses Homomorphic Encryption (HE), Differential Privacy (DP), Multiparty Computation (MPC), Federated Learning (FL), and Trusted Execution Environments (TEE).
Designed for rapid insights on real-world data.
Achieved via Duality SDK, REST API, and integration with leading data warehouses and silos.
Provides complete support for the data science lifecycle, from data ingestion to analysis.
Aids in initial data exploration within the secure environment.
Tools for pre-processing and preparing data for analysis.
Pricing
Countries & Languages
Interface languages
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About SecurePlus
SecurePlus is a secure data collaboration software from Duality Technologies that protects data privacy and security for collaboration among multiple data owners and analyzing parties. It combines Secure Query, Secure Collaborative AI, and Duality Assistant Agent so users can effectively analyze sensitive data while maintaining strict privacy standards. The platform also supports Secure Federated Analytics and is open source to foster community collaboration and transparency. SecurePlus enables organizations to access valuable insights from sensitive datasets without compromising individual privacy. Key capabilities: Secure Query Secure Collaborative AI Duality Assistant Agent Secure Federated Analytics Open Source Best for: organizations that need secure data collaboration and privacy-preserving analytics.
SecurePlus Details
SecurePlus's In-App Market Place
Does SecurePlus have an in-app market place?
Yes
How many Mini-Apps in the marketplace?
1
Mini Apps
N/A
Pricing Options
Accepted Payment Currencies
USD ($), EUR (€), GBP (£), JPY (¥), AUD (A$), CAD (C$), CHF (chf), CNY (元), SEK (kr), INR (₹), SGD (S$), HKD (HK$), NZD (NZ$), KRW (₩), RUB (₽), ZAR (R), BRL (R$)
Pros & Cons
- Advanced privacy technologies: Uses Homomorphic Encryption, Federated Learning, MPC, and more to protect sensitive data
- Encrypted data analysis: Enables SQL-like queries, machine learning, and analytics without exposing raw data
- Flexible collaboration: Supports cross-border, multi-party data sharing with granular access controls
- Enterprise-grade scalability: Handles large datasets and integrates with existing infrastructure via SDKs and APIs
- End-to-end lifecycle support: Covers ingestion, schema alignment, transformation, and analysis in one platform
- Compliance by default: Built to meet stringent data privacy regulations across industries
- Trusted by major organizations: Partners include AWS, Intel, Oracle, IBM, and DARPA
- Complex setup: May require technical expertise to configure cryptographic workflows and integrations
- Performance trade-offs: Encrypted computations can be slower than traditional methods depending on use case
- Limited public adoption: Still emerging in mainstream enterprise environments compared to legacy platforms
- Specialized use cases: Best suited for regulated industries like healthcare, finance, and government
SecurePlus's Support Options
Email Address
info@dualitytech.comContact
+1 917 300 0764Documentation
https://duality-tech.document360.io/SecurePlus's Alternatives
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