This is STELGIC.
Smart trading with AI Agents. Our cutting-edge platform combines the power of AI with robust features engineering for trading automation in financial markets.
Build & deploy AI agents in financial markets
Train and deploy enhanced trading agents on CEX and DeFi, with capabilities to switches between strategies or suspend execution based on specific market conditions.
Auto-generate new trading strategies ideas & portfolio
Users prompts can be translated into new portfolio recommendation or strategy ideas based on assets fundamentals, tokenomics and others data features.
Explorative insights & live signal execution
Conduct explorative data analytics, market insights and live signal execution with autonomous AI agents.
Platform Development Roadmap
AI-Powered Quantitative Research platform
Integrate, training and back-testing AI/ML strategies that performs well in the market, as an autonomous trading system requires advance approach with great flexibility for faster the iteration and fine-tuning process.
AI Prompting and Scripting.
Rich data analytics & Insights, as well scripting capabilities using Interactive AI.
With interactive Prompting and Coding we establish a powerful tool to perform exploratory data analytics, visualization, insights and many others operations.
Finding instruments correlation, market condition, and perform portfolio optimization are few of many use cases.
With interactive Prompting and Coding we establish a powerful tool to perform exploratory data analytics, visualization, insights and many others operations.
Finding instruments correlation, market condition, and perform portfolio optimization are few of many use cases.
Patterns & Features Engineering
Multi-domain algorithms capabilities for patterns and features engineering to enhance AI/ML strategies prediction accuracy.
With high performance capabilities and data processing parallelism, the platform handles large dataset efficiently and as well great flexibility for parameters fine-tuning
With high performance capabilities and data processing parallelism, the platform handles large dataset efficiently and as well great flexibility for parameters fine-tuning
