The problem Apecity solves

Give user freedom to decide it's token's pricing nature and bonding curve equations.

Problem: user have to use typical single pricing bonding curve that is supported by particular token creation platform
Solution: by using some maths and few past reseach, with implementation of apecity customized pricing curve feature, user now can has ability to implement their own appropriate bonding curve which suits their particular usecase.

Problem: Generally used bonding curve follows uniswap curve, which takes very low pricing at the starting of token, which is in nature of FPMM (X*Y=K), which gives token dev power to control and buy very high amount of token amount at the earliest which is not good sign. mostly ruggpull happens this way.
Solution: With few customization to curve, user can prevent this properties. also provided few charts gives very real idea and prediction of market.

Challenges we ran into

Hurdle: quite challenging complex maths equation implementation at the smart contract level with solidity
Solution: Used fixed point library ABDKMath64x64 and reduced little precision
Failures(Learning): Tried PRBMath but couldn't make it with it

Hurdle: Multi chain support
Solution: Used envio for data indexing to make indexing development process very fast, development friendly and hosted service which made our process easier to concentrate on business logic (so similar to graph tho)
Failures(Learning): The graph, have to host our indexers on cloud

Hurdle: Figure out edge case which was not mentioned in research paper.
Solution: Found 1 solution at the medium article written for detailed explanation of Bancor research paper 2017

Additional Features

Project before hackathon was mainly just frontend skeleton, detailed research and implementation plan.
We implemented all dynamic/custom natured pricing curved logic, multi chain indexer support and frontend integration at the hackthon hall only.