CerebroCore AI Architecture
CerebroCore AI is built upon a layered, modular architecture designed to support scalable, secure, and decentralized interaction with intelligent agents. The system is designed to separate concerns between AI logic, access control, user governance, and integration.
🧱 1. Modular Agent Layer
At the core of CerebroCore is a network of modular AI agents, each trained or optimized for a specific function (e.g. coding, art generation, tutoring). These agents are:
Stateless, task-specific, and interchangeable
Prompt-driven, compatible with LLM backends (like GPT, Claude, or open-source models)
Customizable, via user preferences or NFT Access Passes
Sandboxed, ensuring safety and context isolation
Each agent lives within a secure API environment and can evolve through reinforcement learning or community contribution.
🔐 2. Access Control Layer
CerebroCore uses a token-gated access mechanism to interact with agents and platform features. Key components:
$CCAI token for access rights
Wallet login (e.g., MetaMask, WalletConnect)
NFT Access Passes to unlock personalized agents or premium usage tiers
Usage credits for interaction frequency, customizable per agent
Access to APIs, dashboards, or external integrations is always on-chain verified, reducing fraud and misuse.
⚙️ 3. Execution Layer (API Gateway)
All agent interactions are routed through a secure Execution Layer which includes:
Rate limiting & metering based on token ownership
Interaction logging (optionally anonymized)
Webhooks & WebSocket endpoints for live integrations
Multi-model backend routing (choose which LLM to use per task)
This layer acts as the interface between users, developers, and the agent framework.
🧬 4. Customization & Personalization
Users can personalize their AI agents through:
NFT-bound traits (e.g., tone, expertise, behavior presets)
Custom datasets or prompt memory (stored off-chain or encrypted IPFS)
Interface preferences per user (text/voice)
This enables users to build persistent, agent-like AI personalities with unique characteristics tied to their wallet or NFT identity.
🌐 5. Integration & Developer SDKs
CerebroCore is designed to be extensible via:
Public APIs for frontend apps, bots, or tools
Agent SDK for building and hosting your own AI agent
Webhook triggers to connect AI output to 3rd-party workflows (e.g., Discord, Slack, Zapier)
We plan to support integrations with platforms such as Notion, Figma, GitHub, and Telegram for seamless workflow automation.
🗳️ 6. Governance Layer (DAO)
Decisions around platform updates, agent evolution, and ecosystem funding are managed via on-chain governance. This includes:
Proposal system (submit + vote using staked $CCAI)
Treasury management for grants, audits, or bounties
Community-curated agent marketplace
Open roadmap voting (prioritize which agents to release next)
Staking and participation incentives ensure governance remains active and inclusive.
🧩 7. Data Privacy & Security
We prioritize user safety and transparency:
No PII storage by default
Encrypted prompts if stored temporarily
Open-source smart contracts on Ethereum
Audited AI model APIs
Verifiable agent outputs (via prompt signing)
Optional ZK-integrations are being researched for future privacy guarantees on agent interactions.
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