The problem Predictor solves

Forecasting Tool - Current closed group surveys and interviews are clogged with bias and hence affect correct output. Decentralized Prediction Markets act as a perfect forecasting tool in predicting future events be it politics, sports or climate change as people participating make more rational decisions as their decisions are private and anonymous

Monetize Knowledge - There are only limited ways to monetize one knowledge apart from doing our jobs. Prediction markets with predictions in various themes provide an opportunity to monetize one's knowledge.

Creating Awareness - As per the game theory, Predictions based on climate change will make people research more on climate than a news article on climate as the incentives are provided by prediction markets for understanding the complex concept

Value discovery: Prediction markets helps in discovering values of any intangible asset be it NFT, art etc via the wisdom of crowd principle.

Challenges we ran into

1. Moving from python to smartpy created some initial hiccups especailly sp.int was considered as expression and not as integers for certain operations.
2. Had an issue with FA2 metadata creation, when creating FA2 tokens dynamically . Had to take advice from RQ from smartpy telgram to re-write the logic.
3. JS was treating smartpy integers as large integers and hence needed to ocnvert them to string before displaying.