HeyTraders is a Personal AI Quant for crypto markets, turning natural language descriptions into verifiable trading strategies. It falls under the category of agent-native quantitative operating systems, purpose-built for traders, quants, and portfolio managers who need rapid idea testing and deployment. The core value proposition is compressing the typical workflow—research, backtest, execute—into a single chat loop. Users communicate in plain language, and the AI agent Hetty orchestrates four specialist traders (Chart, Market, Trading, Portfolio) to produce results. This eliminates the need for coding or complex terminal commands, making quant-level analysis accessible to anyone. With open beta and all features free, it lowers the barrier for crypto market participants.
The concrete problem HeyTraders solves is the fragmentation and time cost of crypto trading research. Traders typically juggle multiple screens, data sources, and manual backtesting to validate a single idea. This leads to missed opportunities and emotional decision-making. HeyTraders addresses this by providing a unified workspace where natural language queries trigger instant backtests, chart overlays, and cross-exchange funding comparisons. The pain point of slow, multi-step research is replaced with a 30-second loop. For active traders, every second counts; delays in validating a strategy can mean the difference between profit and loss. By streamlining the process, HeyTraders gives users data-driven confidence before risking capital.
The chart analysis feature, called "Ask on the chart, draw on the chart," allows users to interact with price data conversationally. By typing queries next to candles, users can add indicators like moving averages, draw trendlines, switch tickers and timeframes—all through natural language. For example, "Adding 50-day and 200-day SMA on the BTC 1D chart and marking the crossover" produces the visual overlay instantly. This is useful because it removes the friction of manual charting. Traders can experiment with different technical setups rapidly, seeing results applied directly to the chart. The AI understands context, so subsequent queries refine the analysis without resetting the view. This feature turns charting into a dialogue.
The market feature aggregates data from six exchanges—Binance, Bybit, OKX, Hyperliquid, Lighter, Bitget—into a single matrix view. Users can see funding rates, arbitrage spreads, and liquidation flows across venues in one glance. For instance, querying "Comparing funding rates across 6 venues to find the highest" returns a ranked list with the top asset highlighted. This enables detection of arbitrage opportunities and funding rate plays without manual data collection. The chat then allows deeper dives on any ticker. For traders who operate across multiple venues, this centralized data stream saves hours of switching tabs. It also provides a real-time liquidity context that is critical for execution decisions.
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The trading feature offers backtest and live deployment entirely within chat. Users describe a strategy in plain language, and Hetty runs quick simulations using templates like Signal, Grid, Pair, Cross-Sectional, and Arb. An example shows "Validating an RSI-14 momentum strategy on BTC/USDT 1H, 1-year window" returning Sharpe 1.62, annual +30.99%, max drawdown -6.82%. Results are immediately actionable—one click deploys the strategy live on a connected exchange. This removes the gap between backtesting and execution, reducing friction for algo traders. The templates accommodate various approaches, from mean reversion to pair trading. By integrating simulation and live deployment, HeyTraders ensures strategies are consistent and reproducible.
The overall workflow follows a three-step loop: ASK, THINK, LAND. In ASK, the user types one line of plain language—no keywords or SQL. Hetty then splits the task across specialist agents in parallel (THINK): Chart, Market, Trader, and Portfolio analyze from their own perspectives. Results are synthesized and land on the workspace as chart lines, strategy parameters, or portfolio updates (LAND). The underlying architecture uses HT Script to normalize strategy intent into stable code, and a Compatible Engine ensures backtest results match live execution. This design makes the entire process consistent and reproducible, from idea to execution. The loop completes in about 30 seconds.
Concrete use cases include a day trader who wants to test a moving average crossover on BTC. They type one sentence, receive a backtest with Sharpe and drawdown, and deploy it live on Binance in under a minute. A portfolio manager reconciles balances and P&L across Bybit and OKX by asking Hetty for a summary, seeing daily P&L as "+$642 · +1.1%". A quant researcher compares BTC and ETH on the same chart to analyze the spread, overlaying symbols with a simple query. These scenarios yield outcomes such as faster strategy iteration, transparent portfolio tracking, and cross-asset insights. Users gain confidence from data-backed decisions without manual effort.
HeyTraders targets active crypto traders, algorithmic quants, portfolio managers, and market researchers. It is a web-based tool accessible via Google or Apple login, currently in open beta with all features free. The tech stack includes HT Script for strategy generation and a compatible trading engine that ensures consistency across backtests and live trades. The platform also supports external AI agents accessing its browser surface for quant alpha research. In summary, HeyTraders redefines the trading terminal as a natural-language-driven quant OS, compressing end-to-end workflow into a single chat interface. Its primary value is making sophisticated trading strategies accessible, testable, and deployable by anyone.
Active cryptocurrency traders, quantitative analysts, algorithmic trading developers, portfolio managers, crypto market researchers, and AI/ML researchers building trading agents. The tool is designed for users who need rapid idea validation and deployment across multiple exchanges without coding, accessible via web with Google or Apple login, and currently available in free open beta.