Implementation

Our Live Feed is entirely up-to-date harnessing the power of our rug.ai Managed Node service to provide you instantaneous insights into the blockchain. As part of this, we've allowed users to filter by chain, as well as sort by most recent or most relevant:

Sorting by Most Recent will show you an un-objective insight into the live data stream from our websocket on the chains you've selected.

Sorting by Most Relevant (Coming Soon) filters that data to show you what the largest, or most notable events on-chain have been for the time frame you've selected. This can give you an insight to the importance of on-chain events across a number of different time-frames, which is useful for several purposes. In our Beta Product, you may not see the option to filter this way yet. This is because utilising live user data, we're training our proprietary models to learn what users find as most relevant. As such, the Live Feed is now optimised to show you the most recent events first.

On the Live Feed we've built in the ability to filter blockchains, token events, rug scores and market data, so you can curate a feed of things that you want to see. As a user in crypto, one of our pain points was difficulty in spotting new token events early, whether it was big swaps or changes in liquidity, there are no capable tools that tell us what we want to see, on the blockchain, live. Our live feed changes that, building into live events along with a screener to help you look for or track tokens that might interest you.

We are also planning to embed a screener into our Live Feed page to look for historical results based on sorting features. When building our Live Feed, we wanted the optionality to see historical events, so on our Top Events page, you can click to get access to a screener. As seen above, you can choose your timeframe for specific token events, and sort tokens via market cap, rug score, liquidity, events or even name. This will allow you to parse through tokens to search for things that interest you depending on your preferences. This tool, therefore, allows you to parse through the noise to get to what you, as a user, are interested in seeing historically.

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