Why is VELVET gaining market attention? How does DeFAI advance the integration of AI and DeFi into a new phase?

Over the past year, AI Agents have become one of the most talked-about development directions in Web3. From automated research and intelligent trading to portfolio management, more and more projects have started exploring the practical applications of AI in on-chain finance. As users have higher expectations for operational efficiency and asset management experiences, DeFAI (DeFi + AI) is gradually moving from concept to product competition. Velvet entered the market against this backdrop, bringing the outside world’s attention back to whether AI can become the core gateway to the next generation of DeFi.

Why is VELVET starting to attract market attention?

In the past few years, the DeFi ecosystem has expanded rapidly, but product experience has not improved at the same pace. For ordinary users, completing a full on-chain investment often requires frequent switching between wallets, DEXs, data platforms, yield protocols, and cross-chain tools, keeping learning costs and operational costs consistently high.

Velvet aims to change this experience. According to official information, the platform currently supports multiple mainstream ecosystems, including BNB Chain, Ethereum, Base, Solana, and Sonic, and has launched a Multi-Agent AI Co-Pilot. Users can complete project research, asset analysis, trade execution, and portfolio management through natural language. Official disclosures indicate that the platform has already accumulated more than 100,000 users using related products, and has created more than 10,000 strategy Vaults, with on-chain strategies managed by traders, KOLs, and crypto funds.

Instead of adding more features, Velvet places greater emphasis on integrating research, trading, and management into a single entry point. This product approach reflects that DeFi is shifting from “feature stacking” to “experience optimization,” and the market’s focus is gradually moving from the number of protocols to user efficiency.

How is AI starting to change DeFi’s product form?

The development focus of AI in the crypto industry is shifting. In the early market, more attention was paid to AI models, computing power networks, and infrastructure. Over the past year, however, more and more projects have tried to let AI directly participate in on-chain operations. From analyzing token fundamentals and screening yield strategies to executing trades and managing portfolios, AI Agents are gradually taking over tasks that previously required users to do manually.

Velvet’s positioning reflects this trend. The platform combines an AI Co-Pilot with a trading terminal, multi-chain asset management, and strategy Vaults, hoping users can complete complex operations through natural language rather than using multiple separate tools. This model lowers the barrier to using DeFi and enables AI to evolve further from “answering questions” to “assisting execution.”

Behind this trend is a change in user needs. As the number of on-chain protocols and assets continues to grow, what is truly scarce is no longer information, but how to quickly filter information and make investment decisions. For DeFAI platforms, future competition will increasingly focus on interaction experience, execution efficiency, and product integration capabilities—rather than solely on the AI model itself.

What competitive advantages does VELVET have compared with other DeFAI projects?

As AI Agents have become a popular direction, competition in the DeFAI track has also started to expand from single products to platform ecosystems.

At present, related projects in the market can roughly be divided into three categories. One focuses on AI trading bots, emphasizing automated strategy execution. One provides on-chain data analysis and research tools to help users discover investment opportunities. Another tries to build a complete platform that integrates research, trading, asset management, and development capabilities into one system.

Velvet is closer to the third model. According to the official description, besides the AI Co-Pilot, the platform also offers a multi-chain trading terminal, strategy Vaults, and an open API, allowing third parties to create and manage tokenized DeFi strategies. This means its goal is not only to serve ordinary investors, but also to become the infrastructure for trading teams, KOLs, and institutions to manage on-chain assets.

From the perspective of industry development, in the future, DeFAI’s competitive advantages may no longer be simply about AI features—but about who can connect more public chains, more protocols, and more developers. When an increasing number of platforms have AI capabilities, ecosystem scale, network effects, and user retention capabilities are more likely to form long-term competitive moats.

What challenges does DeFAI face? Can AI truly drive the popularization of on-chain finance?

Although DeFAI has become a new hotspot in the crypto market, this track is still in an early stage of development, and there are still many challenges before large-scale adoption.

First, the value of AI is built on high-quality data and accurate execution. The on-chain market changes quickly and protocols are updated frequently. If AI cannot obtain the latest information in time, or if it lacks sufficient understanding of complex strategies, it may impact analysis quality and execution results. For trades involving real assets, users care more about whether the model is reliable, not just whether the responses are smooth.

Second, user trust remains an important threshold for DeFAI adoption. While natural-language interaction reduces operational complexity, having AI participate in trade execution requires higher standards for permission management. How to balance automated efficiency with asset security, and how to help users clearly understand the basis for AI decisions, are capabilities that platforms still need to continuously improve.

In addition, as more teams enter this track, product homogenization may also intensify. In future competition between platforms, it will depend not only on AI model capabilities, but also on ecosystem cooperation, developer support, and long-term user retention. Based on current development, DeFAI has entered the product competition stage, but it still takes time for a mature business model to form.

What factors will determine the long-term value of VELVET?

For DeFAI projects, long-term value comes more from product usage rather than short-term market sentiment.

According to official information, Velvet has built an AI Co-Pilot, multi-chain trading terminal, strategy Vaults, and API infrastructure, aiming to form a complete ecosystem covering research, trading, asset management, and developer services. If more trading teams, KOLs, or institutions choose to create strategies based on the platform, its network effects may further strengthen.

However, the platform’s value ultimately still needs to be supported by real users and developers. Variables worth continuous attention in the future include the speed of multi-chain ecosystem expansion, iteration of AI features, the extent of third-party developer integration, and the continued growth of strategy Vaults. These factors not only determine platform activity, but also affect the ecosystem’s long-term competitiveness.

For the entire DeFAI industry, the market is shifting from focusing on “whether it has AI” to “whether AI truly improves user experience.” Platforms that can continuously lower usage barriers and improve investment efficiency are more likely to build an advantage in the next phase of competition.

How can you keep following VELVET and the DeFAI market through Gate?

As AI Agents, DeFAI, and on-chain asset management become ongoing market themes, projects related to this space—such as VELVET—may also attract more capital attention.

Users can use Gate to continuously follow VELVET’s real-time quotes, trading volume, market depth, and related announcements, while also observing changes in market sentiment by considering the overall performance of sectors such as AI and DeFi. Compared with short-term price fluctuations, more worth focusing on are product updates, multi-chain ecosystem expansion, developer integration, and actual user growth—factors that typically reflect a project’s long-term development potential more directly.

For investors who want to track the DeFAI track, in addition to following individual projects, they can also combine developments in AI Agents, on-chain asset management, and DeFi infrastructure to understand how this track is evolving from an industry perspective.

Summary

VELVET is drawing market attention not just because of AI as a concept, but because it represents DeFAI moving from proof of concept to product competition. As the on-chain finance ecosystem continues to expand, users increasingly need simpler and more efficient ways to invest, and AI is also shifting from an auxiliary tool to an on-chain operational entry point.

However, DeFAI is still in an early stage of development. In the future, competition between platforms will revolve more around user experience, the developer ecosystem, product integration capabilities, and value-capture mechanisms. For VELVET, what is truly worth continuously monitoring is not short-term market hype, but whether the platform can build long-term competitive advantages through real usage scenarios and ecosystem growth.

FAQ

Is VELVET an AI project or a DeFi project?

VELVET is more suitable to be categorized as a DeFAI (DeFi + AI) project. It combines AI Agents with on-chain trading, asset management, and strategy management to help users improve their DeFi usage efficiency.

What is the difference between DeFAI and traditional DeFi?

Traditional DeFi emphasizes protocol functionality, while DeFAI aims to use AI to simplify research, trading, and asset management processes, enabling users to complete more on-chain operations through natural language or intelligent Agents.

What are VELVET’s competitive advantages?

According to its official positioning, VELVET not only provides an AI Co-Pilot, but also integrates a multi-chain trading terminal, strategy Vaults, and API infrastructure, with the goal of building an integrated platform that covers research, trading, and asset management.

Why is DeFAI attracting market attention?

As AI Agents gradually move from content generation into real execution, more and more platforms are exploring the application of AI in on-chain finance. Lowering operational barriers and improving investment efficiency are considered among the most promising development directions for DeFAI.

What are the key factors that will impact VELVET’s development in the future?

In the long run, factors such as product iteration speed, multi-chain ecosystem expansion, developer integration, growth of real users, and the development of the strategy management ecosystem may all influence the platform’s competitiveness and how much attention it receives from the market.