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Between stocks, crypto, and new tokenized assets, information moves at lightning speed, and even experienced traders can struggle to keep up. AssetSwap AI seeks to help by serving as a AI Copilot for modern financehelping users to analyze, predict and act.
It is designed to work as a digital companion that connect directly to wallets and exchangesperforms real-time backtesting, chain reading and social sentiment, and executes “Prompt-to-Action” trades through autonomous AI Agents.
The platform connects to more than 50 brokers and exchangesincluding Binance
$3.27 billion
Robinhood, and Interactive Brokers.
Copilot of AssetSwap AI helps with four key actions: reading what is happening now will learn from what has already happened, forecast what might come next, and execution trade automatically when the conditions are right.
The Intelligence Loop in Four Steps
The AI Copilot uses a simple but convenient logic:
- Backtest. Users can simulate past scenarios to understand how a strategy would have performed in previous market conditions.
- Present. AI scans live data (eg prices, feelingand trading volume) to give a clear picture of what is happening now.
- Predict. Using real-time data and AI models, the system predicts potential outcomes and helps users prepare for what might come next.
- Automate. Once a strategy looks solid, users can put it to work automatically. The AI can execute trades 24/7, following the parameters it defines.
This continuous loop allows AssetSwap AI to help users trade with logic instead of emotion.
AssetSwap’s AI Agents
AssetSwap AI’s intelligence comes from its own AI Agentswhich are autonomous digital assistants designed for various financial roles. Each agent specializes in a specific area.
For example, Agent Meme scans social sentiment and hype cycles to capture fast-moving meme tokens, while Stockbroker tracks stock and earnings reports in global markets. Meanwhile, Broker agent manages multi-exchange portfolios and coordinates trades between platforms.
Together, they form a network of AI Agents that learn from user preferences, adapt to changing conditions, and provide context-aware insights on crypto, stocks, and real-world assets (RWAs).
Users can find out a full AI Store or build their own agents.
$A7X: Ecosystem fuel
Every action in AssetSwap AI is powered by its native token, $A7X. It serves as the utility and reward token:
- $ A7X can be burned for AI Creditswhich can be used to unlock premium AI tools, advanced market analysis and autonomous trading features.
- $A7X holders enjoy reduced fees, faster execution, and early access to new features.
- For staking $ A7X tokensusers can participate in governance and earn passive income.
Can you get $A7X tokens by joining the ongoing presale, earning through trading rewards (each trade yields $A7X cashback), completing gamified missions in the AssetSwap AI ecosystem, or referring new users to the platform.
The total supply of $A7X is 2 billion tokenswith 77 million (3.85%) circulating at the token generation event (TGE).
The private token sale will take place in 10 roundswith each time increasing by +10% in price. At the time of writing, round 3 is underway.
Early supporters get exclusive access to AI features, governance rights and staking rewards on the Copilot platform.
Predictive insights for smarter risk management
Probably the main strength of AssetSwap AI is risk management. Its predictive AI continuously monitors exposure levels, market volatility and liquidation risks. When trends change, users can receive advance notices or let the Copilot adjust positions automatically to reduce losses.
For example, if a portfolio becomes over-leveraged or a meme token starts showing warning signs, AI can signal it before it becomes a problem.
In general, AssetSwap AI was built on a simple belief: Finance should not be reserved for experts. The platform aims to make complex markets comprehensive, interactive and rewarding by bringing AI and automation to everyone.
It offers an all-in-one ecosystem for users of all types – meme traders chasing the next trend, retail investors learning the ropes, and professional quants testing multi-market models, among others.
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