TACEO Secures €4.8M Seed for Encrypted Data Collaboration

\n Graz-based TACEO secured €4.8 million in a Seed funding round led by Archetype VC.

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TACEO Secures €4.8M Seed for Encrypted Data Collaboration

Graz-based TACEO secured €4.8 million in a Seed funding round led by Archetype VC. This capital injection will scale its infrastructure for secure computation on encrypted data. Additional investors included a16z CSX, Cyber.Fund, A.Capital Ventures, Polymorphic Capital, and several angel investors.

Founded in 2022 by a team from Graz University of Technology, TACEO develops software enabling multiple parties to collaborate on sensitive data without exposure.

Scaling Secure Data Collaboration

The company's "Private Shared State" data model uses coSNARKs, combining Multiparty Computation (MPC) for data protection during computation with Zero-Knowledge Proofs (ZK) for outcome verification. This innovation allows instant verification of encrypted information without revealing the underlying data.

TACEO's technology ensures privacy and transparency, particularly in the AI era. It enables AI large language models and autonomous agents to verify facts and make decisions without accessing personal or proprietary information. The solution also addresses privacy challenges in decentralized finance (DeFi).

The startup previously created the Poseidon hash function and a COVID-19 infection tracking system, demonstrating privacy-preserving cryptography at scale. TACEO also partnered with Sam Altman’s World, building software for its iris matching verification service, which secures biometric data for over 14 million people. This approach offers an alternative to traditional methods like relying on public blockchains or complex custom infrastructure, which often expose sensitive data or lack compatibility.

The new capital will expand TACEO's team and scale its technology. This expansion targets use cases beyond crypto and DeFi, including identity verification, financial services, and broader applications in secure data sharing, contrasting with less private methods such as some forms of Homomorphic Encryption.