Traios.IO

Advisor Performance
Livechat
Sentiment Analysis
Technical Analysis
Manager Analysis
Summay of Analysis
Launch Page

✨ Inspiration

Traios.IO was born out of a desire to bridge the gap between human intuition and machine intelligence in trading. We noticed that while many traders rely on indicators or gut feelings, very few have the tools to analyze both technical and sentiment signals simultaneously, especially with explainability. Our vision was to give everyone a personal AI fund manager—one that not only trades, but also explains every move in clear, human terms.

⚙️ What it does

Traios.IO is an AI trading assistant powered by Large Language Models (LLMs). It combines:

Technical analysis from multiple timeframes (1H/4H/1D)
Daily sentiment scores from financial news and social media
An interactive chat interface that explains why the AI enters or skips trades
Transparent performance metrics: accuracy (>64%), RR (2.04), ROI (40% in 3 months backtest)

It’s designed to make automated, explainable trading accessible to both beginners and professionals.

🧱 How we built it

Backend: Python + FastAPI orchestrating sentiment, technical, and LLM layers
Sentiment Pipeline: Aggregates and cleans news & social signals, mapped to daily timeframes
Technical Engine: Uses TA-Lib for computing multi-timeframe indicators
LLM Layer: GPT-4o prompts designed for explainability and trading logic
UX/UI: Web chat interface for interactive Q&A with the AI
Backtesting Engine: Built from scratch to match AI decisions with historical data, avoiding lookahead bias

We also integrated an investment model with equity + utility tokenomics and a sweat equity scheme.

🧗 Challenges we ran into

Timestamp Uncertainty in Sentiment Data Most news and social content only had date-level granularity, so we had to implement lagged sentiment logic to avoid future-leakage in backtests.
Explainability vs Alpha Generation Making the AI both performant and understandable was a constant balancing act. We tuned prompts to retain reasoning while staying concise.
Data Pipeline Reliability Ensuring daily alignment between price candles and external sentiment feeds required strict consistency checks.
User Trust Building trust with users meant more than showing numbers—we had to give clear, human-friendly rationales behind each trade.

🏆 Accomplishments that we're proud of

Developed a fully functional LLM-powered AI trader with real-time explanation capabilities
Achieved >64% accuracy, 2.04 RR ratio, and 40% ROI in backtests
Designed a sustainable, deflationary utility token model with burn mechanics
Created a smooth, intuitive chat UI that demystifies AI trading logic

📚 What we learned

How to align LLM reasoning with financial logic in high-volatility markets
The importance of prompt design and UX clarity in building trust with users
Deep insight into managing data alignment across multiple sources (price, news, sentiment)

🚀 What's next for Traios.IO

Launching the first live copy trading demo for early users
Expanding integrations to include forex and stock markets
Finalizing the utility tokenomics and preparing for Token Round 1.5
Rolling out affiliate and ambassador programs to grow the user base
Continuing to improve the AI’s ability to learn from past trades and user feedback