The problem Chain Feed solves

The crypto market's intense volatility and rampant speculation primarily benefit experienced investors and hedge funds, often at the expense of ordinary investors. This imbalance discourages individual participation, which is detrimental to the ecosystem's overall health. Additionally, access to crucial on-chain information is either prohibitively expensive and complex through advanced analytics tools or biased and potentially misleading from Twitter influencers. These conditions exacerbate the risks for everyday investors. Our mission is to transform cryptocurrency investment into an enjoyable, profitable venture for all. We are developing an analytics tool designed to democratize access to on-chain information. By providing a curated, simplified, and real-time feed of on-chain data, we aim to empower ordinary investors to make informed decisions and thrive in the crypto market.

Challenges we ran into

Technical challenges

• To extract the data we wanted we first tried using Subgraphs that were already made by other people and we’ve also tried creating our own Subgraphs, but due to it being our first time interacting with The Graph, it was very difficult to know how to create and use them. We overcame this challenge by fully utilizing the Subgraphs made by Messari(huge thanks) and using the playground feature of Subgraph studio to experiment with the schema lists.
• We chose Supabase as our backend techstack. The biggest challenge we faced when we first onboarded on Supabase was modeling different kinds of events into a PostgreSQL Database and we solved this by creating a table for each kind of event and defining one-to-many relationships for shared data like tokens.

Non-technical challenges

• Upon deciding specific on-chain events that we should collect data on, we faced a problem: what are the events that would be of the interest of crypto investors? It was very hard for us because no one on our team was a active trader. We solved this challenge by talking with on-chain traders and finding their trading habbits through thorough interviews.
• A similar problem came up when we started discussing what kind of suggestions should we aim for. We do not have the ability to provide actionable-grade information to our users, but we do have the ability to identify some events where certain consequences are likely. For example, a liquidation event on AAVE means that the collateral( ex. ETH) will be sent to a DEX to be sold. We provide this additional insight for investors to come up with their own interpretation of the event and make educated trading decisions.