MEXC Product Director Vivien Lin said the exchange’s next phase of growth will depend less on feature sprawl and more on how efficiently it can connect users with tradeable opportunities, as she detailed the company’s thinking on fees, listings, RWA products and AI in an interview with BlockBeats.
Lin said MEXC now serves more than 40 million users globally and argued that the exchange’s edge still comes from its understanding of retail traders, its zero-fee structure, liquidity depth and a faster product cycle than traditional finance firms can usually match.
"Infinite Opportunities" is about focus, not just more listings
This year marks MEXC’s eighth anniversary. The company has adopted the brand message "Infinite Opportunities," and Lin said the phrase should not be read as a plan to keep adding assets for its own sake or to turn the product into a large, complicated bundle of functions.
Her point was narrower. As crypto and traditional finance move closer together, she said exchanges should get better at shortening the gap between assets, trading opportunities and users. In her view, the job is to identify where the platform should focus and then create more actionable chances for users inside those specific product and business areas.
How MEXC frames its zero-fee model
Lin described the zero-fee strategy as one of MEXC’s most competitive decisions. She said it helps users in two ways at once: it lowers the direct cost of trading and reduces the psychological hurdle that often stops retail traders from entering a position.
She contrasted that with traditional finance, where fees and slippage can add meaningful friction. At MEXC, she said, zero fees are only one part of the setup. The exchange also puts weight on liquidity, slippage control and overall execution quality so that the user’s total trading cost stays low.
That combination of zero fees, lower practical barriers, lower mental barriers and deeper liquidity is what makes the platform attractive to retail users, she said, adding that MEXC’s user base of more than 40 million globally is closely tied to that long-running strategy.
Listings and delistings revolve around participation and liquidity
Asked how MEXC evaluates whether an asset should be listed, especially in higher-risk segments such as meme coins, Lin said the exchange applies strict spot and futures listing standards and adjusts those standards as the market changes.
Even so, she said two variables matter most at a high level.
The first is user enthusiasm, or participation. Lin said user count often reflects how popular an asset is. A widely held and actively traded asset tends to have more dispersed ownership and broader market participation, which can support healthier price discovery.
The second is liquidity. MEXC looks at whether market makers are willing to support a token and whether the exchange has a practical hedging path. If liquidity is weak, she said, users are likely to face heavier slippage and a poorer trading experience.
The same logic applies when the exchange reviews assets already on the platform. Lin said MEXC keeps watching the number of active traders and whether liquidity remains strong enough for an asset to keep its place as a mainstream trading instrument.
RWA push includes more than 350 instruments
Lin said users are becoming less concerned with whether an asset belongs to crypto or traditional finance and more concerned with whether the asset has value and whether there is an opportunity to profit from price moves.
She said that since last year, users have shown more willingness to trade gold, silver and stocks because those assets are tied to businesses or markets with clearer fundamentals. In response, MEXC this year launched Real Stock products on the spot side and TradFi Perpetual products on the derivatives side.
According to Lin, the goal is to let users gain leverage and price exposure with very low cost and limited friction. She said MEXC has already listed more than 350 RWA instruments, covering indexes, individual equities and commodities such as gold, silver and crude oil.
She added that expanding the menu of assets is only part of the work. Stocks, commodities and crypto each require different analytical frameworks, so the exchange is also trying to lower the information barrier through AI News, AI Strategy and tools that explain what a given token or company actually does.
As an example, Lin said a user could ask in a chat window what SpaceX is, and the system could return an explanation of the company’s business, risks, current volatility and price range. If the user wants to act, the same conversation flow can continue into trade setup, including stop-loss and take-profit parameters.
Why MEXC no longer wants a simple "basic" versus "pro" split
Lin said customization still exists inside the product, but she does not see heavy manual customization as the future. If every demand turns into a custom feature, she said, the product eventually becomes a stack of functions rather than a coherent experience.
Instead, MEXC wants AI to identify user type and behavior first, then shape what each person sees. When a new user signs up, the platform does not yet know whether that person is a beginner or an experienced trader, so it starts with a broad view. As that user asks questions, browses pages and interacts with the app, the system gradually refines its understanding of risk appetite, trading habits and knowledge level.
Lin said this can lead to very different outputs for the same search term. Someone searching BTC as a newcomer might get price updates and plain-language market context. A more advanced trader might be shown options trends, volatility changes or even a quantitative strategy suggestion.
AI is being deployed across user features, internal operations and engineering
Lin divided MEXC’s AI work into three layers: functions users can clearly see, internal systems users do not directly see and infrastructure that improves research and development efficiency.
On the user-facing side, she highlighted Maxi AI Bot and AI Strategy. But she also stressed that many AI functions are already woven into ordinary product flows. She used search as a simple case: a BTC search no longer stops at spot and perpetual prices. It can now surface three major overnight headlines, an available campaign, deposit rates and the current trading range, all in one place.
On the internal side, Lin said operations, site reliability and customer service act as "internal clients." MEXC used to run thousands of campaigns a year, and much of the operations team’s time went into setup work. With AI, she said, campaign configuration time has been cut to under 10 minutes, leaving more room for market analysis and user research.
She also said AI combined with big data has made user profiling far clearer. Once someone enters the app, MEXC can generate AI suggestions about that person’s trading intent, user type and the campaigns or tools most likely to fit. In her view, that reduces the knowledge gap between experienced operators and new team members and helps the front-end user get a more consistent level of service.
AI is also being used to strengthen the exchange’s technical foundation and improve productivity across product and engineering teams, she said.
From Assistant to Copilot to a Financial Operating System
Lin laid out a three-step path for how AI could change trading decisions on an exchange.
The first stage is the AI Assistant. This is the question-and-answer model most users already know: ask what you do not understand, and the system responds like a reference tool or knowledge base.
The second stage is AI Copilot, which Lin said is where MEXC is concentrating now. At this stage, the system is meant to stay close to the user, observe behavior and help with repeated tasks. A trader might ask it to monitor the market and send an alert once price reaches a certain level. Or a user frustrated by poor results could ask AI to review all past trades and flag moments when decision patterns start drifting away from the patterns that once produced profits.
The third stage is what Lin called a Financial Operating System. She described this as the future vision rather than a finished product. In that model, a user could set a profit target for the day, ask the bot to find a strategy and execute it, and only be interrupted if the system encounters a problem.
She said MEXC is now somewhere between the second and third stages. The remaining gap, in her telling, comes from two constraints: AI itself still needs much stronger computing and algorithmic capability, and the product also has to solve performance questions around when to run tasks locally and when to call a large model.
To address that, Lin said the team is studying what she called Harness technology so the system can decide intelligently which requests should go to a local model and which require a larger model, with the aim of improving response speed while keeping costs under control.
Search is turning into a unified gateway
Lin said she expects trading platforms to move away from page-heavy interfaces. Rather than pushing users through a maze of tabs and screens, future products may concentrate more of the workflow into one simplified destination.
MEXC’s current search experience is part of that effort, she said. A BTC query can already trigger products, functions and campaigns, which makes the search bar more than a lookup tool. It becomes an early version of a unified entry point.
Why AI Strategy stands out internally
When asked which feature made her most proud as a product leader, Lin pointed to AI Strategy.
Drawing on her past experience in quantitative trading in traditional finance, she said building a robust strategy with no bugs requires disciplined thinking and real coding effort. Even with AI coding tools now available, she said MEXC’s AI Strategy solves two practical problems at once.
First, it allows users to place strategy instructions in natural language. Her example was a simple rule such as buying when MACD turns and selling when it turns again. The system can expand that short prompt into a more detailed instruction set and route it into executable order logic.
Second, Lin said the product team spent significant time studying historical investment masters, extracting their core methods and developing more than 20 quantitative strategies. For users with no previous quant experience, she said those strategies offer a starting point from which they can adjust parameters and get a first hands-on experience with systematic trading.
TradFi and crypto are not eating each other
Lin’s background spans Morgan Stanley, BNP Paribas, Deutsche Bank, Bybit and BingX. Asked what crypto can learn from traditional finance, she pointed first to risk awareness and then to respect for regulation and market structure.
She said her time as a bank trader exposed her to strict leverage controls and forced her to think carefully about whether leverage was necessary, where stop-loss and take-profit levels should sit and what hidden costs might be involved. That discipline, she said, stayed with her.
She also argued that global products have to be built in a more atomic way. For a headquarters product team, the challenge is to provide a shared technical and product base while allowing local teams to recombine modules according to local regulation and user demand.
At the same time, Lin said crypto should not inherit every habit from traditional finance. A single product launch in traditional finance can take six months to one year, while crypto teams often work on a weekly or even daily cycle. In her view, one advantage for crypto-native firms is that they can bring over complex financial products and iterate on them much faster.
How MEXC distinguishes Real Stock from tokenized alternatives
On the broader question of traditional finance platforms entering crypto and crypto firms moving toward conventional assets, Lin said she does not see a zero-sum fight.
She compared the situation with older debates about decentralized exchanges and centralized exchanges. Neither side eliminated the other, she said. Each went deeper into its own strengths. Lin expects something similar between TradFi and crypto, especially because there is still a large middle ground that has not been fully explored.
Traditional brokerages face dual regulatory pressure when they expand into crypto, which narrows the practical room they have for product design, she said. Crypto exchanges moving in the other direction also face their own set of challenges.
Lin said MEXC’s Real Stock model differs from many other market solutions because it connects directly to compliant, licensed broker-dealer infrastructure in traditional finance and gives users 1:1 exposure to underlying equities. Many alternative models, she said, are mainly based on tokenization.
She added that traditional finance firms tend to be stronger with institutional clients, while retail remains less natural for them. For a crypto-native exchange such as MEXC, she said, retail users are the core specialty: what they want from leverage, product design, service and pace of execution is something the company understands well.
Localization across more than 170 markets
Lin said MEXC serves users in more than 170 markets. Local market expansion and community operations are handled with different playbooks depending on user preferences in each country.
From the product and engineering side, she said the main task is to build the foundation well, turn configurable modules into atomic components and let regional teams assemble local offerings and operating flows that fit both user habits and regulatory constraints.
User demand is shifting toward real assets and cleaner access points
Lin said she entered the crypto sector around 2020, when NFTs were expanding quickly. For a long period, because crypto and traditional finance were difficult to connect from a regulatory standpoint, users had limited access to assets backed by fundamentals or real cash flow. That left the market leaning heavily on rotating narratives and thematic speculation.
She said that changed in a fundamental way starting last year. Users can now gain exposure to companies with recognizable fundamentals, while TradFi Perpetual products offer a more convenient and cheaper route to leveraged exposure. In her view, that gives crypto-native users both better assets and better tools.
Looking ahead, Lin said the key market question will no longer be whether crypto users are trading traditional assets or traditional finance users are entering crypto. The more useful questions will be which platform can connect users seamlessly to all assets and which platform can help them find the subset of assets that matches their investment preferences out of thousands of choices.
She said MEXC tracks sector rotation in that context. When the market turned to AI storage, the team checked whether the exchange and its competitors had relevant exposure. When the focus shifted to healthcare, the team reviewed whether its healthcare equity lineup was complete. The exchange then adjusts its asset coverage in line with market heat, development direction and its own expansion pace.
On the tooling side, she said MEXC has already prepared CCLI, or a command-line interface, for bot users, while human traders can use AI Strategy and Maxi AI Bot. The larger product goal remains the same: a simpler, more unified entrance rather than an experience built around 20 separate pages.
After 40 million users, scale is only part of the story
Lin said it is hard to put a final number on how large MEXC can become, but she noted that the exchange already serves more than 40 million users worldwide and is still growing every month.
Scale alone does not define strength, she said. The harder question is whether the platform can keep serving users well as the market expands. She framed that challenge around professional capability, technical infrastructure and whether the system can eventually support 100 million users and 2 million concurrent sessions.
That, she said, will require successive generations of product managers to sharpen their market understanding, keep respect for market realities and build stronger technical execution. As for the moment when AI can fully assist trading decisions, Lin said she does not think it is far away.