Delta V

DeltaV aggregates data from different sources like Airstack, Etherscan, The Graph, and RPC providers. Developers can track custom smart contract addresses, combine data sources into a single, unified endpoint, and set up alerts. Administrators can use our product to take action based on pre-defined triggers on chain. We use Gnosis Safe and Account Abstraction through Biconomy to automate the executable on-chain actions based on pre-defined triggers.

Here are a few of the use cases administrators can use our product for:

1. If price of WETH goes below x price and price of something else goes above x price, swap token in my wallet to other token
2. Anytime an nft collection floor price drops below a certain amount buy the NFT
3. Buy a token when the moving average of the last 10 days is an uptrend by x%
4. If person does above a certain volume, give discounts to users. Dynamically adjust the product based on behaviorally activity in the system. 
5. If price of token asset goes above a certain amount, drop the yield in the pool. Give a discount. 
6. Give discount for certain # of people who did an action. If 100 people did an action on chain, you can trigger a function on your own contract. You need to build discount attribute to your contract. 
7. Dynamically raise or lower liquidity pool of pair. Adjust the game based on how many times interacted with it or doing things.
8. Once a certain amount of token sold, trigger contract and move to stage 2 and price goes to X. Off chain thing and don’t have to code in contract*
9. If address A does something and APY is above x amount, do something
10. If bitcoin below number and person does action, give them x amount $
11. First 100 people to mint a collection, get 2 nfts instead of 1 
12. Automatically lend if APY raises a certain amount across chains. DeltaV routes orders to the correct chain 
13. Anytime an nft collection floor price drops below a certain amount buy the nft

The bottom line is that Web3 data is messy, and APIs only partially cover required data. Hard-coding data sources is time-consuming and requires a lot of maintenance. Across 20 companies we surveyed, we found it takes an average of $100K to set up the initial data pipeline and $54K per year for ongoing maintenance.

We used data from airstack, the graph, etherscan, and RPC providers. We created a global data model across events to allow developers to merge data across data sources. We especially focused on time series data because as developers ourselves we found that is really lacking in many data sources. We wanted to build machine learning models on top of the data and take actions off the predictions but we didn’t get the time. We allow the developer to configure custom endpoints based on their custom workflow and which data sources they want to pull data from. 
 Then, administrators can take real-time action off this data. We used Gnosis Safe and Biconomy’s SDK to automate the executable on-chain actions based on pre-defined triggers that the user sets up in their dashboard. It works like an if, then statement. I.e. If I’m about to be liquidated, my smart contract wallet can pull liquidity from another location on chain and prevent my liquidation in a specific asset. Or, I could use DeltaV to reward users with on-chain tokens or NFTs. Since we pull in on-chain data from a variety of sources including custom smart contracts, we can help companies target their competitors’ users by rewarding them on-chain.