Graz-Based Startup TACEO Secures $5.5 Million in Seed Financing

The privacy-tech landscape is evolving as Graz-based startup TACEO announced a successful $5.5 million seed financing round. The investment, finalized in August 2025, underscores a growing market demand for technologies that allow organizations to process sensitive information without compromising data security or relying on centralized trust.

Advancing Private Execution on Digital Rails

Founded in 2022 by a team originating from the research group of Professor Christian Rechberger at the Graz University of Technology, TACEO focuses on building software that enables multiple parties to collaborate on sensitive data. The startup’s core mission is to create a “Private Shared State,” a model that allows for secure computation without exposing the underlying information.

The technical foundation of TACEO’s platform relies on a cryptographic tool known as coSNARKs. This architecture integrates two distinct approaches:

• Multiparty Computation (MPC): Protects data while it is being processed.
• Zero-Knowledge Proofs (ZK): Provides verifiable proof of outcomes without revealing the input data.

By combining these methods, TACEO aims to provide a private execution layer for various sectors, including finance, identity verification, and AI-driven applications. This allows autonomous agents to pay for services or verify credentials while keeping strategies and sensitive inputs hidden from public view.

Strategic Growth and Investor Support

The seed round attracted significant attention from prominent venture capital firms. The investment was led by Archetype, with participation from a16z CSX, Cyber.Fund, A.Capital, and Polymorphic, among other key partners. The legal advisory for the transaction was provided by the law firm Schoenherr, with partner Thomas Kulnigg highlighting the milestone as a key transaction for their venture capital team.

TACEO’s leadership team, consisting of CEO Lukas Helminger, COO Stefan Plank, and CTO Daniel Kales, plans to utilize the funding to further develop its suite of privacy services. The company currently offers production-ready tools, including OPRF (Oblivious Pseudorandom Function) for private recognition, OMap for private lookups, and specialized proof generation services.

Key Takeaways

• Funding: TACEO successfully raised $5.5 million in a seed round led by Archetype.
• Core Technology: The startup utilizes coSNARKs to enable private computation on encrypted data.
• Use Cases: TACEO’s services support private identity verification, decentralized financial operations, and secure AI agent coordination.
• Origins: The company was founded in 2022 by researchers from Graz University of Technology.

The Future of Private Computation

As digital infrastructure continues to expand, the ability to maintain confidentiality while extracting value from data has become a critical challenge. TACEO’s approach—enabling shared systems to compute on encrypted data—addresses a fundamental tension between the need for data utility and the imperative of user privacy.

With its seed financing secured and its core tooling already live, TACEO is positioned to play a significant role in the development of “digital rails” that prioritize security by design. Whether through enabling payroll and treasury management on-chain or facilitating private AI transactions, the startup’s technology offers a glimpse into a future where collaboration does not require the sacrifice of sensitive information.

Frequently Asked Questions (FAQ)

What is a “Private Shared State”?
A Private Shared State is a data model that allows multiple parties to compute and collaborate on shared information without exposing the actual data to other participants or central authorities.

What are coSNARKs?
coSNARKs are a cryptographic tool developed by TACEO that combines Multiparty Computation (MPC) and Zero-Knowledge Proofs (ZK) to protect data during computation while providing verifiable results.

Which industries is TACEO targeting?
TACEO is currently focusing on sectors that require high levels of data privacy, specifically identity systems, decentralized finance, and autonomous AI agents.