Let the AI trade for you!
TraderAI is a project which utilizes AI algorithms to create different allocation with portfolios for Crypto Projects, divided by sectors / types, in which users can invest their funds and get a higher return than by just investing into a single Crypto Project!
Our Recent Works
Why Choose Us
Token Use Cases
Users will need to hold a certain amount of tokens to access the features and services provided by the DAPP.
Users will need to pay a small transaction fee in tokens for every trade made on the DAPP.
Token holders will be able to receive rewards or bonuses for participating in the community and contributing to the project.
Presale & Airdrop
Presale End on
Listing CEX at March 5, 2023.
Min Buy 0.01 BNB = 100 TraderAI
Max Buy 5 BNB = 50,000 TraderAIBUYGet Ref Link Copy
Research and Development
Professional Trader Selection
Testing and Optimization
Maintenance and Updates
Initial token allocation: 50% for the public sale, 10% for the team and advisors, 20% for community incentives & liquidity, 10% for seed round investors.
Total token supply
1 million tokens (1 000 000)
Token initial price
BEP-20 (Binance Smart Chain)
Token holders will have the ability to vote on important decisions related to the project, such as the selection of professional traders, the development of new features, or changes to the algorithm. This will allow the community to have a say in the direction of the project and increase the alignment of interest of the token holders and the project.
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The AI Mechanics
The AI algorithm in the TraderAI project will work by analyzing historical trading data and identifying patterns and trends that are indicative of successful
strategies. This can be done using a combination of supervised learning and reinforcement learning techniques.
AI algorithm performance will also depend on the quality and relevance of the data used to train it, as well as the quality of the algorithm implementation
and the parameters chosen. Additionally, the AI algorithm will be continuously monitored and backtested.