FutureFlows aims to solve several problems associated with traditional prediction markets.
First, traditional prediction markets are often subject to manipulation and biased information, as participants may have incentives to spread false information or engage in market manipulation to profit from their positions. FutureFlows addresses this issue by using a decentralized oracle system to verify the outcome of events, ensuring that accurate information is used to determine payouts.
Second, traditional prediction markets often face regulatory challenges, as they may be classified as gambling or investment instruments and subject to complex legal frameworks. By using a decentralized blockchain platform, FutureFlows avoids many of these regulatory challenges and allows users to participate in prediction markets from anywhere in the world.
FutureFlows also differentiates itself from other prediction market platforms by focusing on a wider range of markets related to social political issues, such as election outcomes, rather than just financial markets. This focus on social and political issues allows FutureFlows to serve as a decentralized platform for crowdsourced forecasting and opinion aggregation on a wide range of issues and concepts.
Admin(Deployer) Address of FutureFlow :0x0c2892735c4d7536
We initially struggled to comprehend the mechanics of the Flow Blockchain. But the workshops helped a lot and We quickly became proficient in writing Cadence scripts and queries.
We lost half a day in integrating card payment method using USDC. It feels good to have finally succeeded but we hope the team works on to provide concise and to the point documentation.
Another challenge faced was the poor documentation available for implementing a custom wallet authentication function.
We also encountered difficulties when it came to integrating the fcl-js library with our code, as we were using it on the backend of our nodejs app. Nevertheless, the dev support team came to the rescue and now its working fine!
Challenges we're dealing with as we scale:
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