Zypher Network has formed a new collaboration with Nebulai, a decentralized AI agent Marketplace and Compute Infrastructure Provider. The collaboration includes the recording of Zypher Trust Technologies in the Nebulai platform to offer a verifiable and privacy-preserved environment for the development and use of AI agents.
🤝ZYPHER Network × Nebulai!
We are delighted to announce a new partnership with @nebulaihq, a decentralized AI agent Marketplace and Open Compute Network that allows users and developers to work together, implement and intelligent agents with Real-World utility in Scharen.
– Zypher – Network (recruitment) (@zypher_network) 22 July 2025
Nebulai offers an opening -free calculation infrastructure. This web-based platform grants Crowd-Source access to offer computing power to AI algorithms, image returns and privacy-sensitive calculations such as zero knowledge certificates (ZK) and multi-party calculation (MPC) without special hardware and configuration.
This network will enable transparent and auditable performance of AI processes based on the integration of Zypher’s Zero-knowledge trust technologies, such as proof of prompt and ZKTLs.
Zypher Network proposes trust-based AI agent coordination
Zypher -core technologies made with the idea of decentralized AI applications, will enable Nebulai users and developers to verify the actions and effects of AI agents. With proof of promptly, AI reactions can be linked to initial import and ZKTLS provides cryptographic evidence of data integrity in agent-external information exchange.
Cooperation is an urgent requirement of verifiability in decentralized AI processes. The integrated solution can offer a guarantee for Real-World scenarios, because the interactions, how the agents coordinate with each other, are sealed. It can also make it easier to contribute to AI by reducing the confidence barrier for contributors.
Expansion of access to developers and practical user scenarios
The partnership will add value by bringing Nebulai and Zypher together to help with the rise of privacy retention AI solutions. Both organizations have open calculation and verifiable implementation options. AI agents can now be used in a safe, decentralized environment with inherent transparency by developers.
This collaboration also broadens the scope of feasible AI applications that are carried out in trustless institutions, including autonomous coordination and privacy-sensitive calculation. Consequently, it encourages the wider application of AI in highly regulated and sensitive data bulbs.