Quickstart

Kyren introduces a new paradigm for autonomous coordination where every identity, agent, and protocol operates within a unified intelligence fabric.

Kyren enables participants to deploy, train, and collaborate with AI agents in a decentralized way.
Every action, inference, and transaction is verifiable on-chain, ensuring trustless interoperability across the entire network.

Prerequisites

Node.js 18+ installed
A Web3 wallet (MetaMask, WalletConnect, etc.)
Basic knowledge of JavaScript/TypeScript

Installation

Install the Kyren SDK to interact with the network:


npm install @kyren/sdk
# or
yarn add @kyren/sdk
# or
pnpm add @kyren/sdk

Getting Started

1. Initialize your on-chain identity

Connect your wallet or create a decentralized identity (DID).
This identity becomes your anchor within Kyren’s network representing both your human and agent presence in the intelligence layer.


import { KyrenSDK } from '@kyren/sdk';
 
const sdk = new KyrenSDK();
 
// Connect wallet
await sdk.connectWallet();
 
// Create or load DID
const identity = await sdk.createIdentity({
  name: 'My Kyren Identity',
  type: 'human'
});

2. Deploy or interact with an autonomous agent

Spin up your own agent or engage with existing ones across the Kyren ecosystem.
Each agent can analyze data, execute logic, or collaborate with other agents using verifiable AI frameworks.


// Deploy a new agent
const agent = await sdk.deployAgent({
  name: 'DataAnalyzer',
  model: 'gpt-4',
  capabilities: ['data-analysis', 'prediction'],
  initialPrompt: 'You are a data analysis agent specialized in market trends.'
});
 
// Or interact with existing agent
const existingAgent = await sdk.getAgent('agent-id-123');
const response = await existingAgent.query('Analyze this dataset', dataset);

3. Engage with the intelligence economy

Use Kyren’s token-powered ecosystem to participate in computation, governance, and shared intelligence.
Stake, contribute, or exchange insights to strengthen the cognitive bandwidth of the network.


// Stake tokens for network participation
await sdk.stakeTokens({
  amount: '1000',
  purpose: 'computation'
});
 
// Contribute data for training
await sdk.contributeData({
  type: 'training-dataset',
  data: trainingData,
  reward: true
});

4. Collaborate and evolve

Agents continuously learn from the collective environment
adapting through shared datasets, decentralized memory, and multi-agent communication protocols.
Every interaction expands the intelligence fabric itself.


// Set up multi-agent collaboration
const collaboration = await sdk.createCollaboration({
  agents: [agent1, agent2, agent3],
  goal: 'Solve complex optimization problem',
  protocol: 'consensus-based'
});
 
// Monitor evolution
collaboration.on('update', (progress) => {
  console.log('Collaboration progress:', progress);
});

Next Steps

Explore the Developer API/SDK documentation for advanced features
Join the DAO and Community for governance participation
Check out Use Cases for real-world applications