Unlock secure collaboration on sensitive assets. Leverage any data type with any model to generate the insights you need. From simple analytics to advanced AI model training, run computations on data that was previously inaccessible—all while maintaining security and control.
By using secure centralized AI collaboration, Duality allows organizations to access sensitive data and train machine learning models without revealing sensitive information, PII, or model IP.
Many organizations have models that need to be customized to clients, but the sensitivity of their data and that of the model itself prove to be major obstacles. Duality helps organizations create and scale new revenue streams with a workflow that protects both model IP and input data.
Duality ensures you have complete authority over your data. Our solutions allow you to control access, specify the computations performed, determine the operational frequency of the data, and more. Remove the trust from collaborative machine learning model training, tuning, and customization.
The Duality Centralized AI engine integrates confidential computing technologies (Trusted Execution Environments, or TEEs) into our secure data collaboration platform, enabling teams to focus on extracting value rather than managing security complexities.
Harness the latest in confidential computing to address key ML SecOps challenges, including data governance, model IP protection, transparency, monitoring, and explainability.
From project management and encryption to attestation and data ingestion, Duality leverages cutting-edge cloud technologies from leading CSPs to power secure, multi-party data collaboration.
With Duality, AI and ML teams across industries can leverage a wide range of data science, statistical, and machine learning models while ensuring robust protection for both models and input data. This empowers teams to streamline data acquisition, enhance model performance, and deliver greater value by safeguarding sensitive client data.
Support any model and any data type (e.g. Linear, Logistic, XGboost, CNN , LLM etc..)
Apply pre-processing script or transformation to prepare the data to perform model training, inference or any statistical computations.
Meets the requirements of the EU AI Act in both the requirements of an AI Regulatory Sandbox and in simplifying the means for AI providers to acquire real-world data with which they must prove model efficacy and compliance.
Ensure full control and governance of input data, decide who accesses the data, which computations can run, at which frequency, and more while providing continuous integration and delivery of updates to your ML infrastructure.
Like most models, there are often multiple datasets that will be used for training. Easily link datasets based on a unique ID/PII or based on multiple quasi-ID/PII parameters (e.g., name, address, date of birth…).
When training on 3rd party data, it’s common to need to move the data to the model, or the model to the data. Secure Collaborative AI enables models to be run wherever the data resides while protecting both the model IP and input data.
Improve generative ML workflow and model performance by training, tuning, and validating ML models on encrypted data.
Optimize efficiency by working collaboratively across borders and accessing new high-value data sets while meeting data privacy and residency requirements.
Analyze sensitive medical data across centers to gain deeper insights to speed research and discovery.
Protect sensitive data and models while transitioning ML workloads to the cloud.
Apply third-party analytics and ML models to your sensitive data without exposing it to deliver personalized user experiences while preserving privacy.
Proving value to clients is critical for sales teams to effectively drive adoption. Scale model monetization efforts with a workflow that allows clients to input their data for model customization with guarantees of data protection and governance.
Empower your organizations to share and analyze encrypted data using Duality’s Privacy Enhancing Technologies (PETs) such as Fully Homomorphic Encryption, Federated Learning, Trusted Execution Environment, and more…
Enable privacy-preserving data collaborations across your entire financial ecosystem.
Protect patient data across your healthcare network through privacy-preserving collaborations.
Transform your marketing strategies with data collaborations that respect privacy, driving digital advertising efforts with confidence and creativity.
