Home > web3.0 > Pyth Network and The Open Network (TON) Announce Strategic Partnership to Bring High-Fidelity Data to TON Ecosystem

Pyth Network and The Open Network (TON) Announce Strategic Partnership to Bring High-Fidelity Data to TON Ecosystem

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Release: 2024-08-15 03:45:09
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This collaboration aims to bring high-fidelity, real-time data to the rapidly growing TON ecosystem.

Pyth Network and The Open Network (TON) Announce Strategic Partnership to Bring High-Fidelity Data to TON Ecosystem

Web3 data network Pyth has announced a partnership with The Open Network (TON) to bring high-fidelity data to the TON ecosystem.

Pyth’s oracle service will now be available to developers building on TON, aiming to enhance the capabilities of TON-based applications, especially in decentralized finance and gaming.

Pyth’s real-time price feeds are expected to enable DeFi projects to create more sophisticated financial services with the speed and accuracy needed for a global audience.

“We’re excited to partner with TON to bring high-fidelity data to their ecosystem,” said Pyth Network in the announcement. “This collaboration will enable a new generation of decentralized applications to be built on TON, powered by the fastest, most efficient, and most reliable data in Web3.”

Pyth Network, a Solana-based project, is focused on providing decentralized, high-quality, and low-latency data for Web3 applications. The network aims to be a single source of truth for critical financial data, such as foreign exchange rates, cryptocurrency prices, and DeFi token prices.

Pyth’s data is pulled from a network of professional traders, exchanges, and market makers, who contribute their data feeds to the network. The data is then aggregated and validated by multiple nodes before being made available to applications.

This partnership marks the latest in a series of collaborations between Pyth and other blockchain networks. In March, Pyth announced a partnership with the zkSync Layer 2 network to bring its data services to zkSync-based applications.

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