Meet WhiteMind: AI for Trading by WhiteBIT
In trading, there is always more data than time to analyze it. Current price, historical P&L, drawdown, trades, risk, volatility, market regime — each metric on its own shows only part of the picture.
To evaluate an asset or a trading strategy, it is important to understand not only how much it made in the past, but also how that result was achieved, what level of risk it involved, and under what market conditions.
WhiteMind is AI for trading with its own database that analyzes historical market data and trusted crypto sources and works with trading patterns — recurring market scenarios that turn a single prompt into a trading strategy ready to launch.
Instead of manual research, dozens of tabs, and comparing metrics by hand — one request to WhiteMind.
Not AI that knows everything. AI that knows trading.
How WhiteMind differs from general-purpose AI
WhiteMind specializes in the crypto market, trading, and WhiteBIT products.
It does not search the entire internet for answers. Instead, it works with a defined set of specialized sources: current and historical market data, information about crypto assets and trading pairs, and the WhiteBIT knowledge base.
This allows WhiteMind not only to explain what a particular asset, indicator, or strategy is, but also to bring relevant data together in the context of a specific trading request.
For example, instead of looking at historical return as a standalone figure, you can assess it alongside max drawdown, trade structure, risk, and strategy behavior under different market conditions.
Historical metrics do not predict future market behavior or guarantee results. They show what happened in the past and provide additional factual context for making your own decisions.
For beginners and experienced traders
WhiteMind does not require the same level of knowledge from every user.
If you are new to trading, you can ask questions in plain language. WhiteMind can explain terms, help you understand which metrics to focus on, and show why two strategies with the same return may still have very different risk levels.
If you already trade actively, WhiteMind helps you work faster with strategies from its database: evaluate their P&L, drawdown, and trade streaks, as well as find options based on your budget, leverage, and risk level.
For beginners, WhiteMind makes trading data easier to work with. For experienced traders, it speeds up the analysis.
What can WhiteMind do?
Brings market context into one answer
Ask about assets, trading pairs, price action, historical performance, or other market metrics.
WhiteMind finds relevant data and brings it together around a specific request, so you do not have to manually compare information from multiple sources.
Explains trading and market mechanics
Leverage, liquidation price, funding, P&L, maximum drawdown, long and short positions, trading strategies, and other concepts can be discussed just like in a regular conversation.
WhiteMind adapts its explanations to the context of your request, without requiring you to go through dozens of guides on your own.
Knows WhiteBIT products
WhiteMind works with WhiteBIT’s knowledge base and can answer questions about balances, deposits, the trading terminal, trading mechanics, and other platform features.
Helps you work with trading strategies
A single return figure does not show how consistently a strategy achieved its result. For strategies in the WhiteMind database, you can assess a broader set of historical data: P&L, maximum drawdown, profitable and losing trades, result streaks, risk level, and behavior under different market conditions.
This helps you understand not only what historical result a strategy showed, but also under what conditions that result was achieved.
Finds strategies based on your parameters
WhiteMind takes your budget, leverage, and risk level into account to find up to three relevant strategies.
For each strategy, you can review its historical characteristics and compare the available options before launch.
If there is not enough relevant data or a request falls outside WhiteMind’s area of specialization, it does not attempt to fill the gaps with fabricated information.
More than historical P&L
Imagine two strategies in the WhiteMind database with the same historical return.
The first may have generated results gradually over dozens of trades with a relatively smooth equity curve. The second may have spent most of the period in drawdown and generated a significant share of its result from just a few strong market moves.
Based on the final percentage alone, they may look identical. In terms of risk profile, they can be completely different.
That is why WhiteMind helps analyze a strategy not by a single number, but through a broader set of characteristics:
- historical P&L;
- maximum drawdown;
- profitable and losing trades and their streaks;
- realized and unrealized P&L;
- risk level;
- strategy behavior under different market conditions;
- strategy logic and entry and exit conditions.
Where possible, WhiteMind evaluates these metrics in the context of the user’s parameters. For example, drawdown can be considered in the context of a selected budget and leverage, while potential results are viewed based on the parameters of a specific strategy.
Pattern Genome: How WhiteMind finds trading strategies
The strategies available to WhiteMind users are created in advance and go through a separate validation process before being added to the database.
At the core of the WhiteMind strategy database is Pattern Genome — a system in which potential trading strategies are formed from recurring patterns identified across years of market data.
The process starts with finding trading patterns — market scenarios that can be described using clear and testable conditions.
Individual patterns and their combinations form Pattern Genome — a space of thousands of potential strategies that can expand as new market data becomes available.
But identifying a pattern is not enough.
A strategy is first constructed and then goes through a separate validation process. After validation, it may be added to the WhiteMind database. WhiteMind then selects strategies from this database based on the user’s parameters.
How is a strategy validated?
Pattern discovery and performance validation are separated.
Once a potential strategy is created, it is tested on historical periods and market regimes that were not used during pattern discovery or parameter tuning.
Testing on independent historical data helps distinguish a persistent pattern from a result that may have occurred by chance or due to excessive overfitting to past data.
Finding a pattern is not enough — it must also hold up on data that was not used to build the strategy.
Only combinations that pass this validation process are added to the strategy database.
WhiteMind then uses their historical characteristics during analysis: performance, risk, drawdown, P&L structure, profitable and losing trade streaks, and behavior across different market scenarios.
From a prompt to choosing and launching a strategy
WhiteMind is a WhiteBIT product, so researching, evaluating, and launching a strategy are all part of the same workflow.
To get started:
- Open Trade → WhiteMind and set a budget for your strategy.
- Ask a question in plain language or choose one of the suggested prompts.
- Review up to three suggested strategies and their historical metrics.
- Compare their parameters, risk profile, and historical performance.
- Choose a strategy and separately confirm its launch.
- Track its performance in My Strategies: here you can view budget, realized and unrealized P&L, equity, open position, entry price, estimated liquidation price, and other metrics.
- Stop the strategy whenever you choose. It may also stop automatically when predefined conditions are met.
A strategy cannot be launched simply by sending a message in the chat. Launching is always a separate action that requires explicit confirmation through the interface.
Up to three strategies can run simultaneously.
How WhiteMind works with funds
For every strategy you launch, WhiteBIT creates a separate isolated sub-account.
Once confirmed, the specified amount in USDT is transferred to that sub-account, and the strategy operates independently from the rest of the user’s assets.
This isolates the budget allocated to a specific strategy from the remaining funds in the account.
When the strategy is stopped, any open positions are closed, and the remaining funds, including the trading result and after applicable fees, are returned to the main balance.
Less searching, more trading context
WhiteMind does not make trading decisions for the user and does not guarantee strategy performance.
Its purpose is to shorten the path between a question and the data needed to make your own decision.
For some users, that means understanding what is behind max drawdown or liquidation price. For others, it means quickly comparing several strategies by P&L, risk profile, and behavior across different market regimes.
Market and historical data, asset information, WhiteBIT knowledge, Pattern Genome, and trading strategy details — all within one trading workflow.
Instead of dozens of tabs, one request. Instead of a standalone number, context.
The decision is yours. The context is WhiteMind.
This material is provided for informational purposes only and does not constitute personalized investment or trading advice. Do not invest funds unless you are prepared to lose them in full. Investing involves a high level of risk, and protection against potential losses may be limited or unavailable.
