Agentic Oracle
AI-driven decentralized price feeds on Sonic—secure, precise, and reward-based. Nodes earn ERC-20 tokens for accuracy, anomalies are penalized, and users subscribe for real-time, trustless price data.
Created on 14th February 2025
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Agentic Oracle
AI-driven decentralized price feeds on Sonic—secure, precise, and reward-based. Nodes earn ERC-20 tokens for accuracy, anomalies are penalized, and users subscribe for real-time, trustless price data.
The problem Agentic Oracle solves
Traditional price oracles suffer from several critical flaws:
Traditional price oracles suffer from centralization, manipulation risks, and lack of incentives for accuracy. Many existing solutions either charge high fees or fail to penalize incorrect data submissions.
Our Solution
Our AI-driven decentralized oracle on Sonic is designed to eliminate centralization risks, improve accuracy, and incentivize truthful price submissions.
Key Features
1️⃣ AI-Powered Price Aggregation
- Our system utilizes AI Agents to fetch price data from multiple trusted sources.
- Ensures a high degree of accuracy and eliminates single-source dependency.
2️⃣ Incentivized Validation Mechanism
- Each node must register and submit price data.
- Smart contract enforces a 5% tolerance rule – nodes submitting prices within this range are rewarded.
- Anomalous nodes are penalized by reducing their stake or restricting further participation.
- Accurate nodes receive ERC-20 rewards, ensuring a self-sustaining economic model.
3️⃣ Smart Subscription Model
- Developers and dApps that require price feeds can subscribe to the oracle feed for a fixed monthly fee.
- Ensures a cost-effective and reliable price data source.
4️⃣ AI Chatbot Integration
Users can interact with an ML-based chatbot to:
- Stake & Unstake Tokens
- Redeem Rewards
- Fetch Real-Time Price Data
- Predict Future Prices using AI models
This This simplifies interactions for both technical and non-technical users, makiprice feed management effortless.
Use Cases
✅ DeFi
- Reliable price feeds for lending & & borrowing platforms.
✅ Automated Trading Bots
- Trading bots can leverage real-time AI-powered price feeds to make better arbitrage and trading decisions.
Challenges I ran into
NLP Integration with Smart Contracts
One of the biggest challenges I faced was efficiently integrating Natural Language Processing (NLP) with smart contracts. The goal was to allow users to interact with the contract using a chatbot without manually calling functions.
How I Solved It:
- Used ML-based intent detection to classify user queries and extract relevant parameters.
- Implemented a mapping layer that connects detected intent to the right smart contract function.
Tracks Applied (4)