While the crypto market was in decline and the news feed reported one decline after another, my portfolio increased by 160% in 3 months! And it’s not because I’m the best trader out there or that I found a secret Telegram channel that reveals ways to make money. These are the AI signals sent to me by an AI agent who analyzes the market 24 hours a day. Setting up the AI is not that difficult. It can be used as a personal assistant for trading and market analysis.
For example, in September 2025, an AI agent found a token with abnormal on-chain volume and accumulation of whales. This was long before the token pump. This token was MYX Finance (MYX). I bought it for $2,000 as an experiment based on AI trading signals and made $18,000 at the pump. A week after the purchase, the token rose from $1.3 to $14.
I used the AI prompt “Search for tokens with abnormal volumes on the BSC network, filter them by liquidity and concentration in top wallets. » Then, after receiving the token list, I added a clarifying prompt: “Show the top buyers of each token and analyze the smart money and whales over the last 2 days.”
As a result, the AI assistant showed me which tokens had seen volume growth and accumulation from smart wallets, as well as the absence of massive deposits on CEX. So, I found a token that whales had already noticed, but mass investors had not yet seen, because there had been no positive news about the project. However, a typical ChatGPT or Grok would have given something generic like “there has been no positive news regarding the project” or “I have no data to analyze.” Therefore, the main trick is to find an AI with access to blockchain data. And I found it: it’s ASCN.AI.
In this article, I’ll tell you exactly how I use AI Agent to make money in crypto, what AI models I’ve tried, and show you my case studies and work prompts that you can use right now. Let’s go!
How AI Assistants Changed Crypto Trading in 2025
Since AI agents entered the crypto market and the market itself accelerated to its limits, the use of AI assistants among traders has become commonplace. It is physically impossible to analyze hundreds of new tokens and dozens of stories. The enormous amount of information noise on social media drowns out the truly important signals that are difficult to find manually.
With the growing number of cryptocurrency exchanges, funds, and audiences, manual data collection has become extremely difficult. There are too many CEX and DEX exchanges, smart contracts, capital movements between networks and projects themselves.
This is why AI has become an essential tool. Many funds and professional traders already use it. It can handle 90% of routine analysis tasks and become your competitive advantage.
This is why I started looking through different LLMs in search of a working tool.
What AI Crypto Traders Use: From ChatGPT and Grok to ASCN.ai
For those who are not yet familiar with LLM models, they are language models in which you write text and receive a response. The most popular LLM models are ChatGPT, Gemini, Grok, ASCN.AI, DeepSeek and others. They all work the same way. The only differences are in the sources of information and additional features that AI can provide.
The problem with many LLMs is that they are strong in writing text but weak in reading and analyzing blockchain and on-chain metrics. For example, ChatGPT and Grok are good at writing texts and answering general questions. Nonetheless, they are weak in Web3 tasks because they are not connected to blockchain nodes or market data, which means they cannot read transactions or determine the behavior of smart money and funds.
The only tool I found connected to blockchain data is ASCN.AI. He is a specialist AI Crypto Agent trained in Web3 data and, in addition to text analysis, can analyze data, graphs, metrics and transactions. It allows you to:
- Find undervalued altcoins. Ascn can analyze crypto projects in seconds, rather than the dozens of hours a crypto analyst would spend. AI will study the white paper, tokenomics, project news, holder activity and smart money. Perform technical analysis of the chart; determine the likely risks and benefits; and suggest the most efficient time to buy the token and its subsequent sale.
- Among other things, AI can assess the likelihood of a scam or sweepstakes. The robot will analyze the behavior of the project founders, examine the trading patterns on their wallets and provide a summary of potential risks.
- Plus, with API access, you can create your own AI assistant, train it with your analytics technology, and even share it with other users.
After the recent Ascn 1.2 update, the model has progressed significantly, surpassing the most popular LLMs in terms of accuracy and reporting quality.
However, models without node access are also widely used by traders. For example, after updating Gemini to version 3, the model significantly improved its analytical capabilities, so many traders started using it for sentiment analysis. In fact, after the update it became more powerful than ChatGPT, but many traders continue to only use ChatGPT out of habit. If you are one of them, you should broaden your horizons and periodically test new tools, as new LLMs often take the lead.
ChatGPT vs Gemini vs ASCN.ai: Which is the Best AI Agent for Crypto Trading?
To compare different AI agents in practice, I decided to enter the same queries into each and evaluate the quality and depth of the responses. For the experiment, I chose ChatGPT, Gemini and ASCN.
For example, I have a TWT token in my wallet. I haven’t followed it for a long time and want to do a quick search for the latest news, perform technical analysis and make a forecast. I wrote the prompt “Provide a comprehensive analysis of the TWT (Trust Wallet) token. What is the best price to buy and sell it? Analyze regularities, whale behavior and sentiment” and sent it to 3 LLM.
ChatGPT gave the worst result: too much useless information and weak analysis.
Gemini provided a good analysis with relevant information, but lacked depth.
ASCN gave the quickest response, with all the necessary information and good depth. Nothing superfluous.
For the second example, I asked the question “Provide me with in-depth on-chain and market analytics for DezXAZ8z7PnrnRJjz3wXBoRgixCa6xjnB7YaB1pPB263 (BONK): live metrics, top/perp volumes and smart flows, token movements in all key wallets, top holder balances, open positions, inflows/outflows.”
The situation repeated itself. ChatGPT gave a rather banal answer without in-depth analysis.
Gemini was better at analysis than ChatGPT, but still inferior to ASCN in depth and speed.
ASCN gave the most detailed and quickest response.
So ASCN can provide the best answers to Web3 related questions.
How I use ASCN in crypto trading: my use cases
Let’s continue with the case studies. During my latest market research, I noticed bullish sentiment towards the PUMP token in many chat rooms. I started analyzing the token using various AI tools. ChatGPT and Gemini responded that the token was growing, the news was good, and predicted it would go to the moon. They discussed the latest news about the project.
The ASCN, on the other hand, showed the opposite. On-chain data showed that large wallets owned by whales and funds began exiting their positions and selling the tokens at retail prices at the height of the positive news. He also noted that flows on CEX exchanges from private investors had increased and sentiment on social media had become overheated.
Thus, ASCN concluded that the pump was already nearing its end and it was time to take profits rather than opening new long positions. I did not invest in the token and after a few days it started to fall due to high sales volume. I didn’t make any money on this deal, but ASCN helped me anticipate falling prices and avoid losses by resisting the influence of crowds.
Let me tell you about another case. I was looking for a successful trader to start copy trading. I asked ChatGPT“View new Successful Trader wallets (created ≤ 30 days ago), their top purchases, and average holding period.”
However, ChatGPT directly responded that it does not have access to on-chain data and cannot make such a list of wallets.
ASCN I provided a list of wallets in response to the same question: exactly what I needed. ASCN was able to do this because it has direct access to blockchain nodes.
So I got a list of successful traders’ portfolios, selected a few and started replicating their trades. Few copy traders use this method, so you may get better results than public traders, whose trades are copied by hundreds of copy traders, reducing their earning potential to zero.
Why ASCN.AI has become my main crypto-AI assistant
Among all LLM models, ASCN is the best AI assistant for cryptoand it is currently the only model with access to blockchain nodes. This significantly improves the quality of analysis and depth of responses. AI can find profitable trades and provide concrete numbers rather than vague news headlines. Since it was trained on Web3 data, it offers stronger answers than universal LLMs and helps you win even in a declining market.
By registering, you can test ASCN and make 5 free requests. You can ask, for example, “Track where funds reinvested profits after exit (TOKEN): transfer sequences → new positions” or, for example, “Give 3 scenarios for the development of the cryptocurrency market in the next 12 months and how to optimize the investment portfolio for each of them.
ASCN can become your indispensable assistant in analysis and trading. Well, if you’re trading in 2025 and you’re still not using AI, you’re just giving money to those who are. I hope you found my article useful. Good luck!
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