Grant Chain Docs
  • Executive Summary
  • core concepts
    • Problem Statement
  • The GrantChain Solution
  • Technical Architecture
  • Tokenomics
  • AI Model Marketplace
  • Autonomous AI Agents
  • Governance Framework
  • Roadmap
    • Conclusion
Powered by GitBook
On this page

Technical Architecture

A breakdown of the layered components that power GrantChain’s AI-native infrastructure.

GrantChain is built as a modular, AI-first execution layer — purpose-designed to integrate intelligence directly into the core of the chain.

Here’s how the stack is composed:


🔻 1. Base Layer: Solana

GrantChain uses Solana as its high-performance, low-latency settlement layer.

Why Solana?

  • Sub-second finality

  • Low fees

  • Proven throughput

  • Massive developer ecosystem


🔁 2. GrantChain Layer 2

The actual GrantChain protocol runs as a Layer 2 rollup optimized for AI compute.

Features include:

  • Custom rollup architecture

  • Native zkML proof support

  • Model & agent state separation


⚙️ 3. AI Execution Engine

A custom WASM-based runtime that:

  • Executes AI models inside contracts or agents

  • Interfaces with uploaded model files (e.g., LLMs, predictors)

  • Emits zkML proofs for every inference (optional)

This lets you run models like predict_risk() or summarize_vote() inside smart contracts — verifiably.


🧠 4. Model Storage Layer

AI models are stored via:

  • IPFS or Arweave for large model files

  • On-chain metadata registry for versions, ownership, and licensing

  • Optional zk commitments for deterministic verification


🛠 5. Autonomous Agent SDK

GrantChain includes a built-in SDK for:

  • Defining agents with mission-based logic

  • Binding agents to models via on-chain registry

  • Managing autonomous updates, upgrades, and treasury access

This makes launching autonomous agents as easy as deploying a smart contract.


🗳 6. Governance Layer (DAO + AI Copilot)

Governance is handled via:

  • DAO-style token voting with $GRANT

  • AI Copilot that suggests proposals based on protocol data

  • zkML-simulated impact modeling (coming Q4 2025)


🧬 Component Overview

Component
Role

Solana

Base layer for settlement and security

GrantChain L2

Rollup for AI logic and smart agent execution

AI Runtime

On-chain WASM inference with zkML support

Model Storage

IPFS + on-chain index for accessible AI models

Agent SDK

Framework for building and running AI agents

Governance

Token voting + AI recommendations


With this modular, AI-optimized architecture, GrantChain makes real-time intelligence and agent automation natively on-chain — scalable, composable, and secure.

PreviousThe GrantChain SolutionNextTokenomics

Last updated 4 days ago