Built to be simple and intuitive
Log in securely, build queries easily, retrieve insights immediately
Built on state-of-the-art privacy and encryption technologies emerging from years of world-class research, our software solutions feature a highly efficient quantum-resistant combination of secure multiparty computation and homomorphic encryption, that we term multi-party homomorphic encryption (see Multiparty Homomorphic Encryption from Ring-Learning-With-Errors for details), powered by our award-winning Lattigo library.
Design, run, export, repeat
Build your analytics workflow, share it with your partners and collectively run analyses. Export the results and automate the process by connecting your existing tools to our API.
Tailored solutions for your secure data collaborations
From analytics to machine learning, from on-premise to cloud, we have a solution for you
Analytics & Aggregate Statistics
Create collective dashboards of your key performance indicators to draw a global picture in your field and make informed decisions.
Unlock the power of advanced collective analytics with larger sample sizes for your statistical and probabilistic models.
Machine Learning & Artificial Intelligence
From regressions to neural networks, efficiently train models based on collective knowledge to make better forecasts, classifications and predictions.
Deploy Tune Insight on premise, within the infrastructure where you currently keep your sensitive or confidential data.
Our hybrid solution accommodates flexible secure data collaborations where some organizations prefer on-premise deployments combined with cloud services.
Our cloud solution powers secure data collaboration between organizations that already trust cloud providers with their sensitive or confidential data.
Based on advanced research
A platform built on world-class technology
Tune Insight solutions stem from years of peer-reviewed research
The following list of publications highlights the advanced research Tune Insight is born from. It comprises low-level system descriptions and an early evaluation of our patent-pending system using multiparty homomorphic encryption (MHE) for regressions and neural networks, fundamental articles about the underlying MHE framework and its security, novel cryptographic optimizations that break the zero-sum game between security and efficiency, a legal mapping of our technology to data protection regulatory frameworks such as GDPR, and example applications at scale in health scenarios.