One-sentence investment research conclusion: Surf Copilot (AskSurf.ai) is a Web3 AI research and execution platform incubated by Cyber (formerly CyberConnect), dedicated to providing cryptocurrency users with real-time, source-traceable in-depth investment research reports and trading execution capabilities by integrating on-chain data, social sentiment, and technical indicators. Currently, it primarily adopts a subscription model rather than a token model.
Project overview and core advantages: Surf Copilot is an AI assistant aimed at Web3, designed to simplify the complex information acquisition and trading execution processes in the cryptocurrency market. Its core advantages are:
AI-driven In-depth Research: Combining real-time on-chain data, technical indicators, and social sentiment analysis to generate structured, high-quality crypto research reports.
Multi-functional Integrated Platform: Providing three modes of fast query (Ask), in-depth research (Research), and intelligent execution (Executor), integrating Crypto Data Hub, reducing the hassle of users switching between multiple tools.
On-chain Execution Capability: The unique 'Executor' mode allows users to trade, claim airdrops, and perform operations across over 40 chains and 300 protocols (such as Uniswap, Aave, Layer3, EigenLayer) using the platform's built-in wallet, achieving a closed loop from research to action.
Professional Team Background: Incubated by Cyber (formerly CyberConnect), the team includes former Coinbase employees and PhDs in AI.
Main Risks and Bearish Points:
No native token, potential confusion risk: The official statement indicates that Surf Copilot does not issue tokens and only provides services through subscriptions. However, there are low-market-value tokens named 'SurfAI' or 'SURF' (on the Solana chain), which can easily mislead investors. This confusion may lead to funds flowing to unrelated projects, harming user interests.
Reliance on user subscription for business model validation: As a SaaS platform, its long-term success depends on ongoing user subscriptions and value delivery, rather than initial speculation driven by a token economic model.
AI accuracy and trust issues: Despite emphasizing source traceability, the accuracy and fairness of AI-generated content still require user verification, especially concerning investment decisions.
Intense market competition: The number of AI tools in the Web3 space is increasing, and Surf Copilot needs to continue innovating to maintain its competitive edge.
2. Market & Sector Analysis
Belonging Sector and Narrative: Surf Copilot primarily belongs to the Web3 AI tool and crypto research/data aggregation platform sector. Its core narrative is utilizing artificial intelligence to solve the problems of information overload, data fragmentation, and inefficient decision-making in the crypto market, becoming the 'ultimate AI assistant in the crypto world' or 'Web3 version of ChatGPT.'
Market Size and Ceiling:
Market Size: The cryptocurrency market is vast and complex, with a growing demand for efficient information processing and intelligent decision-making tools. Whether retail investors, professional traders, or institutional researchers, everyone faces challenges in data analysis. AI has great potential in improving analysis efficiency and discovering Alpha.
Ceiling: As an AI-driven crypto research and execution platform, its ceiling is closely related to the integration and development of the entire Web3 and AI fields. As more users enter the crypto market and AI technology advances, the demand for tools that can provide reliable, real-time, and actionable insights will continue to expand. Its market potential extends beyond data analysis to broader fields such as trading automation and on-chain governance assistance.
Competitive Landscape and Core Moat:
Competitive Landscape: There are various competitors in the sector, including:
Traditional data aggregation platforms: Such as CoinGecko, CoinMarketCap, Dune Analytics, Nansen (some features overlap, but Surf aims to provide more integrated AI-driven analysis).
General AI large models: Such as ChatGPT, Grok, Gemini (Surf emphasizes that its AI model is specifically trained for crypto data, offering more professionalism and timeliness).
Other emerging Web3 AI tools: Numerous small projects are attempting to provide AI services in specific areas.
Core Moat:
Crypto-specific AI models: Using the proprietary Cyber AI model trained specifically for curation and real-time crypto data, not a general large model, thus providing higher accuracy and relevance.
Depth and Breadth of Data: Integrating on-chain activities, derivatives/technical analysis, and social sentiment data, covering over 40 chains and 300 protocols to provide a comprehensive perspective.
Integration of Research and Execution: The unique Executor mode can directly transform research insights into on-chain actions, reducing user operational friction and time costs.
Source Traceability: Each insight comes with the original source and timestamp, enhancing the credibility of information and allowing users to verify.
Team Background: Incubated by Cyber (formerly CyberConnect), the team has experience and funding support in the Web3 social layer and AI fields.
3. Deep Technology Analysis
Core Architecture and Operating Principles: Surf Copilot uses a 'Multiple Sub-Agents Architecture.' It is not a simple LLM encapsulation, but a proprietary model driven by Cyber AI, tailored for the crypto space. Its operating principles include:
Data Fusion: Real-time integration of crypto-specific data from multiple fields, including on-chain activities, derivatives data/technical analysis, and social sentiment.
Multi-agent Collaboration:
Social Sentiment Analysis: Real-time tracking of the opinions and emotions of over 100,000 crypto KOLs on X (Twitter), monitoring changes in market narratives.
Technical Analysis: Equipped with over 200 indicators and derivatives data, providing real-time trend signals and actionable trading insights.
On-chain Tracker: Covers over 40 blockchains, tracking wallet behaviors, token flows, whale movements, and project treasury activities.
Deep Search Agent: Each query scans over 200 websites and the proprietary Surf database, capturing emerging signals and generating research outputs instantly.
AI Report Generation: Based on integrated data and analysis, AI can generate structured research reports, including summaries, highlights, and charts.
Execution Layer: The platform has a built-in wallet, and upon user confirmation, AI can assist in executing on-chain transactions, such as swaps, airdrop claims, and participation in DeFi protocols.
Key Technological Innovations:
Proprietary Crypto AI Model: Not reliant on general LLMs, but builds a Cyber AI specifically trained on crypto data, improving accuracy and timeliness of analysis.
Closed Loop of Research and Execution: Few tools in the market can seamlessly connect in-depth research and on-chain transaction execution; the Executor mode of Surf Copilot fills this gap.
Multi-dimensional Data Integration: Aggregating scattered information from on-chain data, technical indicators, social sentiment, etc., into a unified interface and performing AI-driven cross-analysis to provide comprehensive, real-time insights.
Source Traceability: Each piece of AI-generated information is linked to the original data source, enhancing user trust and verification capability of AI outputs.
Code Quality and Security Audit:
Currently, there is no public information regarding independent security audit reports on the core codebase of the Surf Copilot platform.
[No public data available] Although the project is incubated by Cyber, and CyberConnect as a mature project may have undergone audits, the code quality and security audit information for Surf Copilot as an independent product has not been explicitly disclosed.
In a Reddit AMA, team members mentioned that 'it cites sources, captures real signals, and it really works,' indicating an emphasis on reliability.
Developer Experience (DX):
Surf Copilot, as an AI assistant platform for end-users, primarily focuses on user experience (UX) rather than direct developer experience (DX).
[No relevant information found] Currently, there is no public information about Surf Copilot providing API interfaces for integration by other developers or providing SDK/development toolkits.
4. Product, Ecosystem & On-Chain Data
Core Product Experience:
Intuitive User Interface: Aiming to provide a 'one-stop' smart, clean interface that packages all relevant information, reducing the need for users to open multiple tabs.
Three Core Modes:
Ask (Quick Query): For obtaining lightweight, real-time answers on prices, factual information, market snapshots, on-chain fund flows, and social sentiment.
Research (In-depth Research): The most commonly used feature for complex research questions, generating structured reports that include project research, narrative analysis, and comparative reports.
Executor (Intelligent Execution): An advanced feature that allows users to directly execute trades, claim airdrops, and participate in DeFi protocols on-chain, requiring final user confirmation.
Crypto Data Hub: Provides the 'largest and most accurate crypto database' for integrating curated datasets into user workflows and providing daily trend rankings.
Multi-language Support: Supported English, Chinese, and Korean during the testing phase, enhancing global accessibility.
Ecosystem Map:
The core ecosystem of Surf Copilot is its own services as a Web3 AI research and execution platform.
Technical Integration Partners: Its AI model integrates data sources like CoinGecko Terminal, RootData, as well as data from over 40 blockchains and 300+ protocols, forming a broad technical integration network.
Incubator: Incubated by Cyber (formerly CyberConnect), benefiting from the ecosystem and Web3 social infrastructure of CyberConnect.
Early Participants: The project encourages user participation during the early testing phase to experience AI Q&A and question mining, providing rewards like points and Genesis NFT whitelists to build an early user community.
Key On-chain Metrics Analysis (TVL, DAU/MAU, Volume):
As a SaaS platform, Surf Copilot's core value and user activity are primarily reflected in its platform usage data (such as the number of reports generated, active user count, transaction volume executed) rather than traditional DeFi project's TVL, DAU/MAU, and other on-chain metrics.
Report Generation Volume: During the beta testing phase, Surf Copilot generated 125,000 reports.
On-chain Execution Volume/Protocol Support: Its Executor function supports 40+ chains and 300+ protocols, but specific execution volume data [no public data available].
TVL/DAU/MAU: [No public data available] These metrics are not directly applicable to SaaS platforms. The project's user activity can be measured through the number of subscription users and frequency of feature use, but these data are currently not disclosed.
Strategic Partnerships:
Incubator and Investors: Cyber (formerly CyberConnect) is its most important strategic partner and incubator. Cyber itself has received investments from top VCs like Multicoin, YZi Labs, Animoca Brand, and Delphi Ventures.
Data Providers: Integrated CoinGecko Terminal, RootData, etc., as sources for its AI model's proprietary knowledge base.
5. Tokenomics
Token Distribution and Release:
[Official statement no token]: Surf Copilot officially states that the platform currently does not issue tokens, and its services are provided through a subscription model. In the Reddit AMA, GTM Lead Roy Shen also confirmed that 'Surf has no token.'
[Market exists tokens with the same name, beware of confusion]: Although there is no official token, market queries show that there are tokens named 'SurfAI' (Ticker: SurfAIBuy now) and 'Surf Copilot' (Symbol: SURF) on the Solana chain. These tokens have very low market values (e.g., SurfAI market value is about $9,336.09, SURF market value is about $2.7146), and are unverified. This strongly indicates that these tokens may be unrelated or intended to exploit the project name for speculation, and investors should be highly cautious.
Core Utility of the Token:
[No official token, no core utility]: Since the official platform has no token, there is no officially defined core utility for a token.
Value Capture and Supply-Demand Dynamics:
[Subscription model value capture]: The value capture of Surf Copilot is mainly realized through its SaaS subscription model. Users pay fees to obtain AI-driven crypto research and execution services. The platform's value is closely related to the number of users, subscription revenue, and functionality iterations.
[No official token, no supply-demand dynamics]: There are no supply-demand dynamics based on an official token.
Inflation/Deflation Mechanism:
[No official token, no inflation/deflation mechanism]: There is no inflation or deflation mechanism for the official token.
6. Go-to-Market & Community
Market Entry Strategy:
Content Marketing and KOL Collaboration: Publishing content through platforms like Medium articles and Binance Square, emphasizing the pain points of information overload in the crypto market and collaborating with KOLs for promotion.
Early User Incentives: Offering point rewards, Genesis NFT whitelist, and priority usage rights during the testing phase to encourage early user participation and word-of-mouth promotion.
Free Trial and Discounts: Offering trial codes (like a 3-day PRO membership experience) and early subscription discounts (like 20%) to attract new users.
Emphasizing differentiation: Actively comparing with general LLMs (like ChatGPT, Grok, Gemini), highlighting the advantages of its 'crypto-specific' AI model and real-time data capabilities.
Multi-language Support: Supports English, Chinese, and Korean, aiming to expand its global user base, with a particular focus on the Korean market.
Community Size and Quality:
Beta Stage Performance: Generated 125,000 reports during the testing phase, indicating a certain level of user engagement.
Social Media Presence: Active on social media platforms like X (Twitter), but specific follower numbers and engagement data [no public data available].
User Feedback: Discussions and AMAs on Reddit indicate that users have positive reviews of its functionality and reliability, but there are also concerns about AI accuracy and privacy.
Brand and Marketing:
Brand Positioning: 'AI research and execution co-pilot,' 'the ultimate AI assistant in the crypto world,' 'Web3 version of ChatGPT.'
Value Proposition: Aiming to provide real-time, source-traceable insights for crypto-native users by integrating on-chain data, technical indicators, social sentiment, and in-depth research.
Marketing Focus: Emphasizing its ability to solve information fragmentation, improve decision-making efficiency, provide actionable intelligence, and on-chain execution capabilities as core advantages.
7. Team, Funding & Roadmap
Core Team Background:
Surf Copilot is incubated and built by Cyber (formerly CyberConnect).
Team members include former Coinbase employees and PhDs in the AI field.
Roy Shen is mentioned as the GTM (Go-to-Market) lead for Surf.
[No public data available] Specific names and positions of other core team members have not been widely disclosed.
Investors and Advisors:
Incubator/Main Investor: Cyber (formerly CyberConnect) is the incubator and investor of Surf Copilot.
Investors of CyberConnect: CyberConnect itself has received over $30 million in funding from top crypto VCs, including Multicoin, YZi Labs, Animoca Brand, and Delphi Ventures. This indirectly provides strong financial and ecological support for Surf Copilot.
Funding History:
Investment from Cyber: A report mentions that Cyber invested $25 million in the project, but specific funding rounds and details [no public data available].
Relation to CyberConnect: As it is incubated by Cyber, its funding history may be related to CyberConnect's overall funding strategy.
Roadmap and Future Catalysts:
Early Testing and Official Launch: The project is in early testing stages as of June 2025, with an expected official launch in mid-July 2025.
Data Center and Mobile App: In October 2025, Surf launched a data center and mobile app, allowing users to conduct project research on Surf anytime and anywhere via their mobile devices.
UX Pro Version: Mention of an upcoming UX Pro version and a preview of the upcoming UX features covering BNB, X Layer, Mantle's Golden Dog, and earning Yap airdrop points and weekly $PARTI cash rewards.
Potential Catalysts:
Continuous iteration and innovation of product features: Especially further improvements of the Executor mode and expansion of multi-chain/protocol support.
User growth and subscription revenue increase: Proving the feasibility of its SaaS business model.
Deep integration with the CyberConnect ecosystem: Utilizing the social layer advantages of its incubator.
AI Technology Progress: With continuous optimization of underlying AI models, the analytical capabilities and accuracy of Surf Copilot are expected to improve further.
8. Comprehensive Risk Assessment
Technical and Security Risks:
AI Model Accuracy and Bias: Despite using crypto-specific AI, the AI-generated content may still carry risks of inaccuracies or biases, especially in rapidly changing market conditions. Users may overly rely on AI and neglect their own research.
On-chain Execution Risks: The Executor feature involves direct on-chain trading, where smart contract vulnerabilities, gas fee fluctuations, and slippage may lead to user asset losses. The security of the platform's built-in wallet is also crucial.
Data Privacy and Governance: The platform aggregates a large amount of on-chain and social data, with transparency in data processing, user privacy protection, and data storage security being potential risk points.
Lack of Code Audit: [No public data available] The absence of a public code security audit report increases the potential risk of technical vulnerabilities.
Market and Competition Risks:
Intense Competition: There are numerous competitors in the Web3 AI tools and data aggregation platform sector, including general large models and specialized data service providers. Surf Copilot needs to continue innovating to maintain its advantage.
Market Acceptance: The platform's subscription model rather than a token model requires users to recognize the long-term value it provides in order to achieve sustainable growth.
Macro Market Risks: The cryptocurrency market is highly volatile, and during bear markets, the demand for paid research tools may decline.
Tokenomics Risks:
[Confusion risk due to no official token]: This is the biggest token risk. The official platform clearly states there is no token, but there are low-market-value tokens with the same or similar names (like SurfAI, SURF). Investors may mistakenly regard these unrelated tokens as official tokens for investment, leading to asset losses.
[No public data available] Due to the absence of an official token, there are no risks related to token distribution, release, utility, value capture, or inflation/deflation mechanisms.
Team and Execution Risks:
Team Transparency: Information about core team members (except the GTM lead) is relatively opaque, which may affect trust.
Execution Capability: The team needs to continuously and efficiently execute the roadmap, iterating products and growing users to stand out in the competition.
Dependence on Incubator: As a project incubated by Cyber, its development may be influenced by Cyber's overall strategy and resource allocation.
Regulatory Risks:
AI Regulatory Uncertainty: Global regulations on AI tools are still evolving, especially regarding AI tools involving financial analysis and automated execution, which may face strict compliance requirements.
Cryptocurrency Regulation: Different countries and regions have varying and constantly changing regulatory policies for cryptocurrency, which may affect the platform's operations and user acquisition.
On-chain Execution Compliance: The Executor feature involves on-chain transactions, which may face regulatory scrutiny in the future concerning decentralized finance (DeFi) protocols and asset trading.
9. Valuation & Investment Thesis
Relative Valuation Analysis:
[No public data available] Since Surf Copilot is a SaaS subscription service platform and does not have an official token, traditional valuation methods for crypto projects (like FDV, TVL/MCAP ratios) are not applicable.
Its valuation should reference SaaS industry metrics, such as ARR (annual recurring revenue), user growth rate, user retention rate, unit economics, etc. However, these operational data are currently not disclosed.
Comparing with similar data analysis or AI tools, such as Nansen (data subscription) and ChatGPT Plus (AI subscription), can provide a rough market pricing reference. Its core value lies in its 'crypto-native' AI capabilities and the integrated loop of research and execution.
Complete Investment Logic (Full Bull Case):
Sector Potential: The combination of Web3 and AI is a current hot trend, and the demand for efficient, intelligent analysis tools in the crypto market is rigid.
Unique Product Positioning: Surf Copilot offers a unique value proposition in the information-overloaded crypto market through its crypto-specific AI model and the integration of research + execution functionalities. It addresses core pain points for users, such as switching between multiple platforms, data fragmentation, and low decision-making efficiency.
Strong Technical Background: Incubated by Cyber (formerly CyberConnect), it has an experienced technical team and strong financial support, ensuring the continuous development of the product.
First-Mover Advantage and Data Accumulation: As an early entrant, it is expected to build a data moat through AI training and data aggregation, enhancing model accuracy and insight quality.
Clear Business Model: Adopting a subscription model, it avoids the direct impact of token price fluctuations and is expected to establish a more stable revenue stream.
Detailed Potential Risks (Full Bear Case):
No official token, high confusion risk: The market has multiple low-market-value tokens with the same name, causing severe confusion, potentially leading to investor capital losses and damaging the project's reputation. This is an extremely serious risk that may deter a large number of potential users and investors.
Challenges in Validating SaaS Business Model: The market's acceptance of paid subscription tools needs time to validate, especially during bear markets, where users may prefer free or low-cost solutions.
Intensifying AI Competition: As general large models (like OpenAI, Google) continually enhance their knowledge of the crypto field and plugin ecosystems, along with more specialized AI tools emerging, Surf Copilot's differentiation advantage may weaken.
Regulatory Uncertainty: The on-chain execution feature and AI applications in finance may face strict regulatory scrutiny, increasing operational costs and compliance risks.
Insufficient Team Execution and Transparency: If the team fails to continuously deliver high-quality products or lacks transparency about core team information, it may affect community trust and user growth.
Final Rating and Action Recommendations:
Rating: Neutral to Cautious
Action Recommendations:
For platform users: Surf Copilot, as an AI research tool, has certain innovations and practicality. Users are advised to fully experience its functionalities during the trial period and validate them with their own research, without blindly trusting all AI outputs. For its Executor feature, it is essential to operate cautiously and understand all on-chain risks.
For investors: Direct investment is currently not recommended.
Strongly recommend the team clarify the token issue: The official team needs to make a stronger and clearer statement regarding the absence of a token and actively combat the low-market-value tokens that misuse its name to eliminate market confusion and investment risks. This is key to building trust and fostering long-term development.
Pay attention to its SaaS operational data: Investors should closely monitor Surf Copilot's user growth, subscription revenue, and engagement metrics rather than chasing low-market-value tokens with its name.
Observe market acceptance of Web3 AI subscription services: Monitor the long-term sustainability of its business model.
Monitor regulatory dynamics: Particularly changes in regulatory policies regarding AI in finance and on-chain execution.
