Gajami - Dev Airdrop Verifier

Gajami - Dev Airdrop Verifier

Automating Developer Airdrop Verification : Easier application and settlement with Multichain signature and FastAuth, AI-driven verification, evolving into skill based ZK DID gig market.

The problem Gajami - Dev Airdrop Verifier solves

All protocol look for developers, yet Dev Airdrop is difficult

  • Established Developers increased 16% from 2022 - 2023
  • New Developer dropped 52% from 2022 - 2023
  • Protocol look to airdrop devs for increased engagement
  • Starknet incident: Airdrop Squatters took more more then actual, commiting devs

Painpoint

  • Real User Verification & Eligibility Check
  • Too much hassle to apply & aggregate tokens all over chain

Answer

  • Simple Identity verification & Easier to verify contribution with AI elgibility check
  • One-point data entry to Multichain settlement

Challenges we ran into

Fast-Auth

The FastAuth documentation was well-written; however, following the SDK guide as instructed didn't yield successful execution. Despite seeking support on Telegram, our pain points remained unaddressed. We worked around it by using NEAR official fastauth example instead of the SDK.

Relayer

Multichain gas relayer would have been better, but at the moment documentation for Relayer was quite scant that we could not use it; even though a GitHub repository was added later as a reference, we decided to skip it due to anticipated time consumption. So instead we analyzed the 'pagoda-relayer' source code to understand how it delegates signatures and how it executes signed transactions, and then applied it to our project.

Chain Signature

The Chain Signature documentation was decent, and there were executable example projects available. However, we encountered issues while signing smart contracts on BOS. This was resolved through various attempts on our part, and the feature provided by Mintbase to mint NFTs served as a helpful reference.

Conclusion

In the end, through this focused effort and collaboration, our team successfully integrated the NEAR chain abstraction and AI technology. The experience provided a valuable learning opportunity for all team members and equipped us with the ability to effectively respond to similar technical challenges in the future.

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