Challenge
Turn fragmented market signals into a consistent context, separate model reasoning from financial risk management and give users one product for conversation, monitoring, strategy validation and controlled execution.
FINTECH / AI / TRADING
AI market analysis and trading workflow automation
MLX Trader combines a native AI analyst application with an autonomous trading runtime. The system gathers market data, builds a multi-timeframe Smart Money Concepts context, explains scenarios in natural language and routes automated decisions through deterministic risk controls.
- Python
- FastAPI
- Svelte 5
- Tauri 2
- Rust
- SQLite
- ccxt
- Polars
Why MLX Trader was created
Why MLX Trader was created
A trader must follow several timeframes, price structure, liquidity, derivatives indicators and news at once. MLX Trader brings that context together: it supports conversational market analysis and provides a separate automated runtime for formalized trading scenarios.
Who the product serves
The product serves active crypto traders who want explainable SMC analysis, proactive alerts and a history of market reviews, as well as automated-strategy operators who need backtesting, dry runs, controlled execution and strict risk boundaries.
Solution
We built a shared data and feature layer that evaluates 5m, 15m, 1h and 4h timeframes and identifies BOS, CHoCH, liquidity zones, FVGs and order blocks. FastAPI delivers this context to the AI analyst and native application, while dedicated strategy, risk, broker and scheduler modules run the automated workflow.
Capabilities
Product capabilities
The capabilities support one operating scenario and share common state, control and analytics.
Conversational AI analyst
A user selects an instrument and asks a natural-language question; the system answers from current market context and SMC structure.
Multi-timeframe analysis
The context combines 4h macro structure, 1h context, 15m tactics and 5m timing so that local signals are never viewed in isolation.
Smart Money Concepts
The engine detects swings, BOS and CHoCH events, liquidity sweeps, fair value gaps, order blocks and impulsive moves.
Expanded market context
Price and indicators are enriched with funding, open interest, long/short ratio, Fear & Greed, BTC dominance and recent news.
Proactive scanner
A background process watches structural triggers and extreme conditions, stores alerts and surfaces them in the app and system notifications.
Strategy validation and execution
A separate runtime supports backtesting, paper mode and live execution through a broker adapter after risk guards approve the intent.
Outcome
Outcome
MLX Trader brings market-structure analysis, a conversational interface, proactive monitoring and an automated trading runtime into one product. Users get explainable context for discretionary decisions, while formalized strategies receive a separate path for validation, risk control and execution.
Python
FastAPI
Svelte 5
Tauri 2
Rust
SQLite
ccxt
Polars
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