Swiss startup Tune Insight secures $3.4M funding for privacy-preserving machine learning

Tune Insight enables collective analytics and federated machine learning, protecting data in use.
Swiss startup Tune Insight secures $3.4M funding for privacy-preserving machine learning

Today confidential collaborative analytics and privacy-preserving machine learning startup Tune Insight announced a $3.4m funding round.

The company has developed a platform to orchestrate secure collaborations on sensitive or confidential data across companies, domains, and jurisdictions, enabling collective analytics, federated machine learning or other approved computations while protecting data in use and streamlining compliance.

This helps users automate collective intelligence extraction, reduce data liability, and streamline compliance while re-enforcing data security and privacy.

The company spun out of several years of research at the Swiss Federal Institute of Technology (EPFL) to apply cryptography to personalised healthcare — hospitals wanted to collaborate without transferring or revealing their patient data to others. 

Today, Tune Insight is deployed at University Hospital Zurich, CHUV in Lausanne, Inselspital in Bern, Switzerland, and powers applications such as survival analysis for precision oncology and personalised reference ranges.

The latter application enables practitioners to rely on up-to-date patient reference ranges, based on collective data of 9 million data points from over 250,000 patients, instead of outdated ranges from a less relevant population. 

For University Spital Basel, Tune Insight enables the secure training of dermatology machine learning models on skin images across jurisdictions. 

Tune Insight's solutions are also used in law, financial services and cybersecurity. Tune Insight's platform is also working at extending support for privacy-preserving generative AI. 

Juan R. Troncoso Pastoriza, co-founder & CEO of Tune Insight, shared: 

"The data economy falls short of its promise for valuable, highly confidential or regulated data. In a data-driven world, protecting data not only at rest and in transit but also in-use, is paramount.

There's an increasing need for organisations to collaborate and progress towards more protections for citizens and customer data through regulations like GDPR. Therefore, robust applied cryptography solutions that combine the best privacy-enhancing technologies are of greatest importance in all domains. 

At Tune Insight, our vision is to transform the paradigm of the data economy into an insight economy that better protects sensitive data, that is more secure, fair, and protective of privacy and confidentiality rights".

Alexander Lange, Founding Partner at remarked:

"We believe that AI's bottlenecks won't be software development, tooling or algorithms but access to raw compute and high-quality data sets. 

Tune Insight is making a breakthrough contribution to the latter by building an operating system for model training on confidential data without leakage.

For the first time, adversarial stakeholders operating across multiple levels of a given value chain are economically motivated to collaborate. This will lead to significant efficiency gains and better products for their customers."

14Peaks Capital led the oversubscribed seed funding round with participation of US-based, Debiopharm and Zurich Cantonal Bank. Existing investors Wingman Ventures also participated in the funding round. 

Tune Insight will use its latest funding to strengthen sales and marketing teams, and accelerate international expansion in Europe and the US.

Lead image: The Tune Insight management team  Romain Bouyé, Juan R. Troncoso Pastoriza, and Frederic Pont. Photo: Uncredited.

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