Tradeos Ai

Stock Trading · Free tier

TradeOS AI focuses on turning a trader’s own logic and intuition into 24/7 autonomous agents that watch markets, analyze signals, and act according to rules described in natural language. Instead of hand-coding strategies, traders describe patterns, conditions, and risk preferences in plain English, and the system’s AI models translate that into executable decision engines. Sitting on top of pro-grade data and infrastructure, it aims to give retail and professional traders institutional-style automation and “agentic” workflows without writing code.

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Pricing

Free: $0 per month; includes 2 agents, 15 Pro-Research queries per day (2 credits), 3 Pro trials per day, access to basic AI models, Pro data sources, and full history with real-time data.
Plus: $4.50 per month; includes up to 5 agents, ~500 Pro-Research queries per month (10 credits), 3 Pro trials per day, access to premium AI models, Pro data sources, and full history with real-time data.
Pro: $9.50 per month; includes unlimited agents, ~1,000 Pro-Research queries per month (20 credits), unlimited Pro feature usage, access to premium AI models and institutional data sources, and full history with real-time data.
Ultimate: Custom pricing; includes everything in Pro, plus custom enterprise features, API support, and SLA with dedicated CSM.

Features

Natural-language strategy builder: Describe chart patterns, signals, and conditions in everyday language that the AI converts into executable trading agents.
Multimodal technical analysis: Uses AI to interpret candlestick structures, trends, and chart formations across stocks, forex, commodities, and crypto.
24/7 autonomous agents: Agents continuously scan thousands of assets, monitor conditions, and can trigger alerts or execution logic around the clock.
Unified Open Market for data: Integrates professional data feeds, quant models, and third-party services through TradeOS’s open market infrastructure.
Risk guard and execution controls: Built-in protections around volatility shifts and market regimes, plus a Proof-of-Delivery mechanism to reduce vendor and model-risk concerns.

Use cases

Active Retail Day Traders: Using autonomous agents to track intraday setups so they are not glued to every chart.
Swing and Position Traders: Encoding multi-day or multi-week conditions into rules that run continuously while they are offline.
Crypto and FX Traders: Relying on 24/7 monitoring for highly volatile, round-the-clock markets.
Trading Educators and Communities: Packaging their own playbooks as reusable AI decision engines for students or followers.
Quant Data Vendors and Signal Providers: Plugging proprietary data and models into the TradeOS network to reach more traders.
Uncommon Use Cases: Used by fintech startups to prototype AI trading copilots without building infrastructure; adopted by research teams modeling agent-based market behavior.