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Knowledge Hub

April 16, 2024

Empeiria Unveils End-to-End Verifiable Data Infrastructure (EVDI) Testnet

Empeiria, the trailblazer in End-to-End Infrastructure for Verifiable Data and Trust Services, proudly announces the launch of its first Testnet. With this milestone in developing the first End-to-End Verifiable Data Infrastructure (EVDI), Empeiria reaffirms its commitment to empowering AI-driven organizations with secure, efficient, and privacy-compliant verifiable data solutions.

The Testnet launch comes after more than 15,000 hours of research and development (R&D) by Empeiria’s talented technical team. In order to establish the best market fit for its cutting-edge solutions, the company has engaged in over 70 meetings.

The company has seen a growing interest in its End-to-End Verifiable Data Infrastructure (EVDI), with more than 20 potential customers already interested in deploying this one-click verifiable, interoperable & decentralized data solution. This underscores the increasing demand for easily deployable, secure infrastructure that bridges the gap between Web2 and Web3, enabling organizations to harness the power of data of the future.

“EVDI, the highest value-to-cost infrastructure on the market, will transform digital interactions with cryptographic truth and decentralized trust,” said Marcin Parafianowicz, Founder & CEO of Empeiria. “The goal is to seamlessly bridge off-chain and on-chain worlds, enabling innovative real-world applications with the power of verifiable data,” he added.

As Empeiria continues to lead the charge in simplifying the deployment of decentralized data ecosystems, the company anticipates more exciting announcements soon. Its next steps involve an Empe Mainnet launch in H2 of 2024, the release of a Trust Network Builder and a Cross-chain hub for verifiable data via IBC, as well a token listing and more.

Empeiria remains committed to empowering businesses with easy access to high-quality, structured, and verifiable data, driving transformative changes in business processes and fueling the development of more reliable, efficient, and unbiased AI models.

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