Tune Insight

Tune Insight

Developing prototypes and deploying pilots with early customers in healthcare, e.g. with Swiss university hospitals, in cyber threat intelligence, in insurance risk analysis, and etc.

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DateInvestorsAmountRound
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CHF2.0m

Grant
Total Funding000k

Financials

Estimates*

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Revenues, earnings & profits over time
USD202120222023
Revenues000000000000
% growth-150 %-
EBITDA000000000000
Profit000000000000
EV000000000000
EV / revenue00.0x00.0x00.0x
EV / EBITDA00.0x00.0x00.0x
R&D budget000000000000

Source: Dealroom estimates

More about Tune Insight
Made with AI
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Tune Insight is a startup that operates in the data analytics market, providing a unique solution for businesses to leverage their data without compromising privacy or security. The company's primary clients are organizations that have a wealth of data but are hesitant to share it due to privacy concerns. Tune Insight's technology allows these organizations to extract valuable insights from their data without sharing or transferring it to any third party, including Tune Insight itself.

The company's business model is based on providing a software solution that is deployed at each client's site. This software uses advanced collective analytics and federated learning to prepare encrypted partial results from the client's data. These results are then aggregated by Tune Insight's distributed system to provide powerful insights that only the authorized user can decrypt and use. This allows organizations to make better decisions based on their data, without compromising its security.

Tune Insight's solution is highly scalable, able to manage hundreds of participants, and becomes more precise and valuable as more organizations join the collaboration. It is also fully software-based, meaning there is no need for additional hardware. The company generates revenue by charging clients for the use of its software and the insights it provides.

In terms of compliance and security, Tune Insight's solution is GDPR compliant and is touted as being more secure than traditional federated learning, as data is never transferred or revealed. It also claims to offer better performance than fully homomorphic encryption, a method of performing calculations on encrypted data without decrypting it.

Keywords: Data Analytics, Privacy, Security, Federated Learning, Collective Analytics, GDPR Compliant, Scalable, Software Solution, Data Valorization, Encrypted Data.

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