System Architecture

NeuroCP allows AI agents to operate with both intelligence and context. It’s built on a modular, privacy-first architecture that connects three core layers: the model layer, the intent engine, and the decentralized context layer. Together, these components help the AI understand user goals and respond accurately using the right information.

This design gives developers the flexibility to build on top or modify specific parts of the flow—while staying aligned with key principles like security, decentralization, and user control.

Core Layers of the System

Layer	Description
Model	The AI engine that performs tasks, such as generating responses or analyzing input
Intent Parsing & Routing	The part of the system that interprets what the user is trying to do
Decentralized Context Protocol	A decentralized system that retrieves and supplies relevant user data and preferences
Agent Runtime Environment	Ensures that only permitted models or agents can access specific context data
Cryptographic Attestation & Verification Model	Translates incoming intents into context-aware queries for the AI model
Output Composer	Finalizes and delivers the response based on model output and available context

How the System Works

1. A user makes a request through an AI interface—like a chatbot, dApp, or voice input.

2. The intent engine analyzes the request to figure out what needs to happen.

3. The context resolver gathers relevant data from decentralized sources, such as user preferences, wallet states, permissions, or recent actions.

4. The AI model processes this enriched input to generate a precise, context-aware response.

5. An access control module ensures that all data use aligns with the user’s privacy settings and permissions.

6. Finally, the output composer formats the result and delivers it back to the user.

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Built for Flexibility

NeuroCP’s modular design supports a wide range of use cases—from personal assistants and workflow tools to DeFi agents and autonomous apps. It can interact with both on-chain and off-chain data, making it well-suited for hybrid Web2 and Web3 environments.

By separating logic, context, and permission handling, NeuroCP gives developers the power to build intelligent, privacy-respecting systems—without being locked into a fixed platform or architecture.