DeFi stablecoins protocol Ampleforth launches on Avalanche (AVAX)

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Ampleforth development firm Fragments Inc. announced today the completion of Avalanches integration with the Ampleforth protocol to bring AMPL, the Ethereum-born decentralized unit of account for denominating stable contracts, over to the sixth-largest blockchain in the world.

Since August, the decentralized finance stack on Avalanche’s Layer 1 blockchain has grown to become one of the most robust in the industry, with more than $8 billion total value locked (TVL) across more than 40 decentralized exchanges and lending/borrowing protocols.

And to support the sustainable growth and liquidity of its DeFi ecosystem, Avalanche has worked closely with the Fragments team to bring a more durable and censorship-resistant alternative to stablecoins into the mix.

“It is ironic that the DeFi ecosystem currently relies so heavily on centralized stablecoins for liquidity and lending collateral, explained Evan Kuo, CEO of Fragments, Inc., in a written statement.

With the changing regulatory landscape and uncertainty around what the verdict around stablecoins will be, its important for DeFi to have a financial building block thats decentralized, uncensorable, and have some aspect of price predictability or stability, he added.

How the move to Avalanche helps

AMPL is a fully algorithmic unit of account that acts as a fundamental building block for DeFi. AMPLs can be used to denominate stable contracts without reliance on centralized custodians or lenders of last resort.

Its protocol restores price to its target by transferring the volatility of demand from price to supply, rather than attempting to remove volatility altogether.

This ability to automatically adjust the number of units to bring AMPLs back to their price target without intermediaries unlock many fundamental use-cases for DeFi that span lending, borrowing, and the creation of on-chain derivatives.

Avalanche, on the other hand, has grown in popularity over the past year, with users gravitating towards its instant finality, highly scalable, and cost-effective model.

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