Truflation Pioneers Censorship- Resistant Economic Data – KISS PR Podcast
Truflation has successfully closed its first private token sale, securing the funding required to accelerate its mission to systematize, standardize, decentralize, and democratize the reporting of all financial and economic data, as an on-chain Data DAO.
Truflation’s seed round includes investments from Fundamental Labs, C² Ventures, Balaji Srinivasan and the IBA as well as other private investors with extensive decentralized finance and data industry expertise and influence.
Founded in 2021, Truflation offers independent and censorship-resistant US inflation calculations based on census level price information from more than 30 data sources in real time, as opposed to the BLS (Bureau of Labor Statistics) approach which is based on survey data. This is put on-chain via blockchain oracles and is also accessible through a free public dashboard.
Ryan Emmick, DeFi Lead at Fundamental Labs, said: “Truflation is revolutionizing economic reporting. Using tokenized incentives, they are making it possible to get continuous, accurate, uncensored sources for economic data globally. No longer can the groups causing inflation get away with manipulating the metrics surrounding it. We at Fundamental Labs are proud to be leading the round and helping Truflation to spearhead this issue.”
All Truflation price indexes will be available through Chainlink’s on-chain data oracles for DeFi and Web3 smart contract developers to incorporate into their applications. Truflation is a pioneer Data DAO in the Chainlink ecosystem.
By taking a developer driven approach, data is collected from a large group of different data sources updated daily, tracking the price changes of 10 million items across 12 different categories. In 2022, Truflation plans to release inflation indexes for 5 additional countries as well as launch a wide range of other economic data feeds on-chain.
Balaji Srinivasan, former Chief Technology Officer of Coinbase said:“In times of increasing inflation and unreliable…
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