AI Agents Documentation
Comprehensive guide to implementing and managing AI-powered autonomous agents on the Bloklab platform for automated trading, analytics, and compliance.
Table of Contents
1. Overview
AI Agents on the Bloklab platform are autonomous smart contracts enhanced with artificial intelligence capabilities that can execute complex financial operations without human intervention. These agents combine blockchain technology with machine learning to provide intelligent, automated solutions for trading, analytics, and compliance.
Autonomous Operation
Self-executing agents that operate 24/7 without human intervention
Real-time Processing
Process market data and execute decisions in milliseconds
Built-in Security
Multi-layered security protocols and compliance automation
2. Core Features
Autonomous Trading Agents
Self-executing smart contracts that perform trades based on predefined rules and market conditions.
- Real-time market analysis
- Risk management protocols
- Automated order execution
- Portfolio rebalancing
Machine Learning Integration
Advanced ML algorithms for predictive analytics and intelligent decision making.
- Pattern recognition
- Trend prediction
- Anomaly detection
- Behavioral analysis
Data Analytics Agents
Automated data processing and insights generation for informed decision making.
- Real-time data processing
- Custom reporting
- Performance metrics
- Compliance monitoring
Security & Compliance
Built-in security measures and regulatory compliance automation.
- Multi-signature authentication
- Regulatory reporting
- Audit trail management
- Risk assessment protocols
3. Use Cases
Automated Market Making
Deploy liquidity providing agents that automatically manage bid-ask spreads and inventory.
Portfolio Management
AI-driven portfolio optimization and rebalancing based on risk tolerance and market conditions.
Compliance Monitoring
Continuous monitoring of transactions and activities for regulatory compliance.
Price Discovery
Advanced algorithms for fair price discovery and market efficiency optimization.
4. Implementation Guide
Quick Start
Define Agent Strategy
Configure your agent's trading strategy, risk parameters, and operational rules.
Deploy Smart Contract
Deploy your AI agent smart contract to the blockchain with your specified parameters.
Monitor & Optimize
Use real-time monitoring tools to track performance and optimize agent behavior.
Configuration Example
// Example AI Agent Configuration
const tradingAgent = {
strategy: 'market_making',
parameters: {
spread: 0.002, // 0.2% spread
inventory_target: 0.5, // 50% target inventory
risk_limit: 0.1, // 10% max risk
rebalance_frequency: 60 // seconds
},
conditions: {
min_liquidity: 100000, // $100k minimum
max_slippage: 0.005, // 0.5% max slippage
circuit_breakers: true // Enable safety stops
},
monitoring: {
performance_alerts: true,
compliance_checks: true,
real_time_metrics: true
}
}5. Configuration
Strategy Parameters
- • Trading frequency and timing
- • Risk tolerance levels
- • Position sizing rules
- • Market conditions triggers
Safety Mechanisms
- • Circuit breakers and kill switches
- • Maximum loss limits
- • Time-based restrictions
- • Multi-signature requirements
Ready to Deploy AI Agents?
Start building intelligent autonomous agents for your trading and analytics needs. Our team is here to help you implement and optimize your AI agent strategies.