Built for Autonomy, Not Automation
Most trading systems automate a human process. Trident AI was designed from the ground up to operate without one.
System Architecture
Four layers working in concert to deliver fully autonomous execution.
Market Data Ingestion
Real-time futures data across multiple timeframes
Signal Engine
Proprietary algorithms evaluate entry conditions
Execution Layer
Three-wave deployment across fleet accounts
Risk Management
Exchange-level brackets, trailing stops, position limits
Three Waves. One Signal. Maximum Capture.
When our system generates a trade signal, it does not place one order on one account. It deploys that signal across three waves of accounts at three different price levels.
Wave 1
Based on higher timeframe level signals. Identifies the primary trend direction and enters when conditions align across multiple timeframes.
Wave 2
Triggers when a pullback occurs for a liquidity sweep while the overall trend remains intact. Better entry price, tighter stop, improved risk-reward.
Wave 3
Activates on a deeper pullback for a liquidity sweep or retest of previous lows while the trend remains intact on the higher timeframe. Maximum value capture with no concentration risk.
The result: our backtesting shows the three-wave architecture increases expected value per signal by approximately 77% compared to a single-entry approach. Better entries. Tighter stops. More captured profit.
Five Layers of Defense
Algorithmic trading systems fail when they rely on software to protect capital. Our system does not.
Order-Level
Every trade is bracketed at the exchange. If our software crashes, the stop loss and profit target still execute.
Account-Level
No account participates in every signal. 70-80% participation means the best-performing accounts are naturally preserved.
Wave-Level
Three waves use different accounts. Capital is never concentrated at a single price level.
Fleet-Level
Accounts span multiple prop firm platforms. No single platform failure takes down the operation.
Business-Level
A trained backup operator maintains an independent system instance. Documented succession protocol ensures continuity.
Enterprise-Grade Infrastructure
The system runs on the same kind of infrastructure stack you would find at a mid-size financial services firm, because that is where the founder spent a decade building enterprise systems before launching this.
Cloud Sync
Azure Cloud Services for managing and synchronizing account data via automated cron job scheduling
Fleet Management
Custom-built web application for real-time fleet monitoring and configuration
Investor Report
Custom-built web application for investors to track daily performance of the system across various accounts
Credential Security
AES-256-GCM encryption for all platform credentials
Automated Operations
Node.js automation layer handles account provisioning and data collection
Backtesting Pipeline
Systematic strategy validation with full historical data
Want to see the system architecture in detail?
We share a technical overview with qualified partners.
Request Technical Overview