TradeOS AI

Free

TradeOS AI is a platform for finance work. It lets you build AI agents that watch markets and flag trade setups based on your own rules.

You describe your strategy in plain language. The agent then monitors charts 24/7 and shows you when your conditions hit.

It is built for people who already know what they want to trade but hate staring at screens all day. It is not for people who want buy-and-hold simplicity or proven, verified results.

Open it if you have a manual strategy you want to automate without code. Skip it if you need verified performance data or hands-off trade execution.

It helps most when you want to systematize work you are already doing by hand.

• Traders who want to automate existing strategies without coding: You describe your entry conditions in normal sentences. The agent handles the repetitive chart watching.
• Technical analysts with repetitive chart monitoring workflows: You stop checking the same five indicators across twenty tabs. The agent flags when your setup appears.
• Users who prioritize explainable AI outputs over black-box signals: You see the agent's reasoning, not just a buy or sell command. You decide if the logic holds up.
• Day traders needing continuous scanning and validation: You trade short timeframes. The agent catches moves while you step away.
• Swing traders requiring multi-day tracking and confirmation: You hold for days. The agent tracks your thesis without you updating spreadsheets.
• Position traders focused on long-term thesis validation: You build macro bets. The agent monitors regime shifts that might break your story.
• Traders seeking pre-built strategy frameworks across multiple asset classes: You start from a template instead of a blank page. You fork and tweak from there.
• Prop firm traders needing profit-split tracking across multiple accounts: You run several funded accounts. The platform logs trades and splits automatically.
• Traders using Wyckoff, ICT, Smart Money Concepts, or Price Action methodologies: The AI Coach flags pattern mistakes specific to your approach. You get feedback tied to your system.
• Retail traders wanting automation without coding: You cannot write Python. You still get systematic workflows.

These are the parts you notice after setting up your first agent.

• No-code agent building from plain language descriptions: You type what you want. The system builds the logic. You test it live.
• 1 billion token context window for document analysis: You feed the agent SEC filings or trade histories. It reads and remembers the full document.
• Multi-timeframe analysis in single view: You compare hourly and daily trends without switching windows. You spot conflicts faster.
• White-box reasoning with explainable outputs: The agent shows its work. You trust it more because you see why it flagged the setup.
• 24/7 continuous agent monitoring versus manual chart watching: You sleep. The agent does not. You catch overnight moves you would have missed.
• Telegram integration for mobile access: You get alerts on your phone. You check your weekly summary without opening the full platform.

You build an agent in about fifteen minutes.

1. Describe your strategy in plain English: the assets, timeframes, and indicators you watch.
2. Select from pre-built templates or start from scratch.
3. Review the agent's reasoning on flagged setups and decide whether to act.

Skip it when these limits matter to you.

• No independent performance verification: You cannot check if other users made money. You only have the company's own claims.
• Self-promotional source with no user testimonials: You find no organic reviews or measured results. You test blind.
• Unclear whether platform executes trades or only analyzes: You might still need to place orders yourself. The agent may just alert you.
• Vague differentiation from established competitors: You struggle to see why this beats tools you already know. The "agent-native" framing is thin.
• Beta status with incomplete features: You risk bugs and missing functionality. The product is not fully built yet.