OlaXBT CEO Jason: Using AI + Blockchain to bridge the information gap, allowing retail investors to sleep peacefully with their holdings during fluctuations.

What we need to do is to allow users to sleep soundly amidst the Fluctuation. Article Author: 0x9999in1, MetaEra Having been in the cryptocurrency industry for many years, Jason has experienced the ups and downs of several bull and bear cycles. This veteran, who once worked in strategy and operations at Binance Earn, is now leading the OlaXBT team to explore a brand new path—creating an innovative MCP-driven market using AI and blockchain technology. He understands that retail investors often miss opportunities in the market due to delayed information and inefficient operations, and even become "chives" in the market. It is this pain point that drives him to deeply integrate his accumulated data processing experience with AI technology to build OlaXBT's core competitiveness. Breaking down data silos, on-chain whales can be captured. Jason candidly stated that his experience with centralized platforms made him realize the critical importance of data integration. "In the past at Binance, data from different business lines was scattered like islands, and users had to manually piece together fragmented information." Now, OlaXBT uses blockchain technology to connect on-chain and off-chain data, allowing users to not only track cross-market capital flows in real-time but also to capture the movements of whale addresses. The platform also integrates various data sources, such as market sentiment, whale movements, news, and a series of quantitative trading indicators, and uses an exclusively developed multi-factor analysis model to deduce trading factors that have high correlation with individual cryptocurrencies (this model is currently applying for a patent in the United States). AI Agent: From "Q&A" to "Action" Based on the Model Context Protocol (MCP), OlaXBT has developed its flagship AI agent, the (AI Market Maker). Based on reinforcement learning technology, AI agents that generate real-time alpha signals by analyzing on-chain data, options implied volatility, and social media sentiment are reshaping the trading experience. When a user anxiously asks "can I buy BTC now" in the middle of the night, the AI agent no longer just pushes a generic analysis report, but acts like an experienced trader to retrieve historical price movements, scan the options market (such as the fear index), analyze the spot contangos of major exchanges, and even trace the records of large transfers for nearly 3 hours. Subsequently, users can adjust their strategies according to their personal trading habits and risk tolerance. This "question-as-trade" capability stems from the deep integration of fragmented data in the MCP framework. For example, when a whale address transfers a large amount of BTC to the exchange, the system will combine on-chain data, option implied volatility, and social media sentiment to give a prompt that "short-term selling pressure is high, it is recommended to open positions in batches", liberating retail investors from cumbersome information screening. What's more, the system can automatically trigger the transaction: the user only needs to click confirm, and the AI agent will execute the strategy through the smart contract, truly realizing "ask the question and trade".

Lowering the threshold: Interactive tutorials guide users Despite the powerful tools, Jason is clearly aware of the challenging balance between "professional" and "user-friendly". He shared a product detail: the team designed a layered guidance mechanism specifically. ・Newbie Protection: When real losses exceed 50%, "Comfort Mode" is triggered, popping up funny memes to ease anxiety; ・Mandatory Learning: Before real trading, the system detects the risk score. Users with a score below 60 must complete a 3-minute instructional video; ・Efficient Adaptation: Bilingual interface in Chinese and English, preset trading templates, and interactive tutorials help users quickly master advanced features such as "Minting Personal AI Agents" and "Setting Up Automated Vaults." "Our target users are not complete beginners, but rather those who have some foundation yet are burdened by manual operations," Jason emphasized.

Data Collaboration of Multi-background Teams The team members of OlaXBT have diverse backgrounds: a former investment bank trader responsible for optimizing low-latency systems, a quantitative analyst focused on strategy backtesting, and members from traditional finance exploring the tokenization of stocks in collaboration with Nasdaq. Jason emphasized that team communication follows the principle of "data-driven decision making". For example, before product iterations, new features are first tested on a small scale to collect user click heat maps and operation duration data, and then a decision is made on whether to launch it fully. "Is there controversy? Then let the A/B test results speak for themselves every time," he joked, saying that this agile development model complements the "rapid response" of former investment bank traders with the "modeling capabilities" of quantitative experts, even leading to the creation of a congestion warning mechanism—alerting users to adjust their strategies before the network is about to become congested. Ambition in the Web2.5 Era Looking to the future, Jason replied with certainty: "The boundaries between traditional finance and DeFi will become more and more blurred." He revealed that OlaXBT is exploring two major innovations: labeling U.S. stock earnings data and developing cross-market hedging tools. For example, users can use USDC to trade Tesla stock tokens directly in the future, and AI will simultaneously analyze the semantics of the earnings call (such as the pessimism of the CEO's tone) to generate (for example) a deleveraging prompt. In his view, the transparent data layer provided by blockchain combined with the efficient decision-making capabilities of AI will accelerate the disintermediation of financial markets. "Individual investors use AI agents to capture opportunities such as cross-border exchange rate differences and derivatives pricing deviations, breaking the information monopoly of traditional institutions." "When the transparent data layer of blockchain meets the efficient decision-making of AI, the democratization of finance truly begins." Risk Control: From "Luck" to "Calculable Security" In the face of the high Fluctuation of the digital asset market, Jason emphasized that "a sense of security comes from technology, not luck." OlaXBT's AI risk control system provides users with triple protection through historical backtesting and personalized risk analysis:

1. Personalized strategy matching: Frequent bottom fishers are pushed high fluctuation strategies, while conservatives provide low-risk arbitrage solutions;
2. Dynamic position limit: For those who continuously add to their positions against the trend for three consecutive days, a single position will be automatically compressed to within 5% of total assets;
3. Crisis Warning: The system detects unusual movements of whales in advance and sends users a "Liquidity Withdrawal" alert. "We want users to sleep soundly amidst fluctuations—this sense of security comes from technology, not luck," Jason confidently concluded. Conclusion From the battlefield of centralized strategies to the innovative testing ground of OlaXBT, Jason Chan has always been solving the same problem: how to help ordinary investors survive in the jungle of digital assets. Today, the "weapon" in his hand has upgraded to a double-edged sword of AI and blockchain, and the end of this battle may be just as he said—"When technology bridges the information gap, the true democratization of financial markets will arrive."

About OlaXBT Official Tools: OlaXBT is an innovative MCP-driven market, where its AI agents enhance digital currency trading through reinforcement learning technology, real-time alpha signals, and actionable insights. Users can track KOL sentiment, identify emerging trends, gain early access to high-potential tokens, trade through automated vaults, and mint their own AI agents, all based on on-chain precision, making trading faster, smarter, and data-driven.