Agent-Core Protocol Layer

DeepCore's technical architecture is designed to ensure that the platform has efficient AI agent execution capabilities, scalable application ecology, and decentralized data security. The platform mainly consists of three core products:

1

Agent-Core Protocol Layer

2

DeepMatrix AI Agents Store

3

Developer Toolkit

4

TokenForge Launchpad

Agent-Core Protocol Layer: The Neural Hub of Web3 AI Agent Ecosystem

Agent-Core Overview

The Agent-Core Protocol Layer serves as the foundational technological engine of the DeepCore ecosystem. Functioning as a core hub connecting developers, end-users, and blockchain infrastructure, it provides a standardized technical framework for AI Agent creation, interaction, and collaboration. Through its four-dimensional architecture design, this protocol layer addresses long-standing challenges in Web3 AI Agent development—interoperability gaps, data silos, security risks, and inefficient collaboration—laying the groundwork for explosive growth in decentralized intelligent applications.

The core role of Agent-Core

1. Standardized Agent Interaction Protocol:

Technical Architecture

• Employs a modular API gateway design with a unified Agent communication interface (DAI-Protocol), supporting multi-protocol adaptation for HTTP/3, WebSocket, and Libp2p

• Integrates semantic parsing middleware that automatically converts output formats across AI models (e.g., standardizing responses between GPT-4o, DeepSeek R1 and Claude-3)

• Provides a compatibility testing toolkit with 100+ predefined test cases to validate Agent interaction compliance

Platform Role

• Enables cross-chain/cross-platform interoperability: Agents on BNB Chain can seamlessly interact with DApps on Ethereum, Solana, and other ecosystems

• Builds an open collaboration network: Developers can modularize Agent functionalities into composable "smart building blocks"

• Use Case: A DeFi strategy Agent automatically fetches Chainlink oracle data while coordinating with a transaction execution Agent on Base

1. On-Chain/Off-Chain Data Routing Layer (Oracle Hub):

Technical Breakthroughs

• Innovative hybrid verification mechanism: Combines Zero-Knowledge Proofs (zk-SNARKs) with TEE trusted execution environments to ensure data authenticity

• Constructs a layered data pipeline:

  • Layer1: Real-time synchronization of on-chain critical data (e.g., token prices, smart contract states)

  • Layer2: Caching of off-chain complex data (social media sentiment, IoT data) via decentralized storage networks

• Develops dynamic routing algorithms: Intelligently selects optimal data transmission paths based on network conditions, reducing latency by 40%

Ecosystem Value

• Supports complex application scenarios:

  • Generative AI Agents access on-chain copyright data in real-time

  • Cross-chain derivatives trading Agents synchronize multi-chain liquidity information

• Enables data assetization: Developers can package private data into tradable AI Agents through the data routing layer

1. Secure Sandbox Execution Environment:

Security Architecture

• Three-tier protection system:

  1. Hardware-Level Isolation: Built on Intel SGX trusted execution environments

  2. Smart Contract Firewall: Monitors gas consumption patterns in real-time to detect anomalies

  3. Dynamic Permission Control: Implements zero-trust architecture requiring re-authorization for each Agent interaction

• Proprietary Risk Simulation Engine: Simulates 10,000+ attack scenarios to intelligently generate defense strategies

Platform Advantages

• Ensures data sovereignty: User privacy data is processed via homomorphic encryption, allowing Agents to compute without accessing raw data

• Creates a developer safety net: Automatically blocks malicious contract calls (e.g., an MEV bot attack was detected and neutralized within 0.3 seconds)

• Achieves compliance certifications: Meets GDPR, CCPA, and other data protection regulations

1. HIVE Collaboration Network:

Collaboration Mechanism

• Swarm Intelligence Framework:

  • Task Auction Market: Agents compete for task execution rights via game theory models

  • Federated Learning Layer: Enables collaborative model training across Agents without data sharing

  • Reputation Staking System: Calculates Agent reputation scores based on on-chain behavior records

• Innovative Collaboration Protocols:

  • SWARM Protocol: Sub-second consensus mechanism for high-frequency trading scenarios

  • HARMONY Protocol: Byzantine fault-tolerant collaboration framework for complex decision-making

  Ecosystem Empowerment

  Sparks new business models:

  • DeFi scenario: AI Agents will validate each other and automatically form strategic alliances, increasing the expected revenue in the Defi domain by 300%.

  • Alpha project research and judgment scenario: AI Agent group generates AIization similar to Nansan, Arkham, GMGN and other comprehensive platforms through multiple data platform

  Build a self-evolving ecosystem: Collaborative networks will generate knowledge sharing events to drive continuous Agent iteration.