AI-powered, on-chain hackathon evaluation with stakes, verifiable scores, and wallet-native flows.
Hackathons promise innovation—but their evaluation systems are often centralized, inconsistent, and non-transparent.
Despite building real, working products:
- Developers often receive subjective feedback due to limited judging bandwidth.
- It’s difficult to provide fully transparent and verifiable evaluation at scale.
- Self-assessment isn’t typically integrated into the process, missing an opportunity for deeper reflection and benchmarking.
- Results are usually event-bound, with limited long-term visibility or verifiability.
In contrast to transparent, high-stakes talent formats like India’s Got Latent—where participants own their confidence and results are visible—many hackathons still rely on opaque, off-chain decisions with no skin in the game.
How can we build a fully on-chain, AI-powered evaluation system for hackathons that is:
| Goal | Meaning |
|---|---|
| Decentralized | No sole reliance on a centralized judging authority for record-keeping and settlement |
| Verifiable | Scores, outcomes, and rewards recorded on-chain |
| Scalable | AI reduces judge bottlenecks using real project signals |
| Incentive-aligned | Participants stake value that reflects confidence (self-score vs eventual judge/AI score) |
- Developers connect wallets and submit projects (GitHub + live demo).
- They stake ETH via smart contracts (real on-chain transaction on Ethereum Sepolia).
- AI evaluates submissions from real URLs (repo + hosted site), not mocks.
- Scores are compared with self-assessment (1–10) in the product experience and results UI.
- Verified scores can be submitted on-chain via backend + agent flow; winners can claim through the contract where applicable.
- Wallet integration is required for user-signed txs
