VerticalScope Conference Call Summary Company Overview - **Company Name**: VerticalScope (OTCPK: VFOR.F) - **Industry**: Online Enthusiast Communities - **IPO**: Listed on TSX in 2021 - **Registered Members**: Over 70 million [2][3] Core Business Model - **Revenue**: $66 million in the last twelve months with $25 million EBITDA [3] - **Cash Flow Efficiency**: Nearly 90% EBITDA conversion to cash [3] - **User Engagement**: Core users are enthusiasts contributing over 2.3 billion posts [4] Strategic Advantages - **Tech Platform**: Utilizes a tech platform and data assets to unlock value through AI [1] - **Community Focus**: Dedicated spaces for niche interests, leading to high-quality content [5][6] - **Competitive Moat**: Authentic user-generated content and volunteer moderators enhance community engagement [5] Market Trends - **Evolution of the Web**: Transitioning from static content to social platforms, now entering the "Agentic Web" phase where AI systems require structured human-generated content [9][10] - **Data Quality**: High-quality data is becoming the currency in the new web landscape [10] Growth Drivers 1. **Direct Traffic Expansion**: Focus on growing direct audience connections, leading to three times higher engagement compared to search traffic [12] 2. **AI Product Innovation**: Leveraging AI to enhance user experience and engagement, including the introduction of an AI community assistant named Fora Frank [13][17] 3. **New Revenue Sources**: Exploring immersive brand experiences and data-driven revenue products, with advertising making up around 80% of total revenue [14][24] 4. **M&A Strategy**: Actively pursuing acquisitions of independently run communities to enhance growth [15][22] Financial Position - **Debt Reduction**: Reduced net debt by $46 million, achieving a net leverage ratio of 1.2 times [29] - **Flexible Debt Structure**: $100 million revolver with attractive rates [29] - **Cash Generation**: Strong cash flow supports growth and capital allocation strategies [30] Revenue Model - **Digital Advertising**: Primary revenue source through programmatic ads and direct sales [24][25] - **E-commerce**: Contributes under 20% of revenue, including affiliate revenue and subscriptions [26][27] - **Marketplace Revenue**: Recent acquisition of the Ritual food pickup app has driven double-digit growth in commerce [28] Leadership Changes - **CEO Transition**: New CEO appointed in June, with continued involvement from the founder as chair [31] - **Promotions**: Key leadership promotions to strengthen operational capabilities [32] Summary - VerticalScope is positioned for growth with a solid foundation, focusing on direct traffic, AI innovations, and strategic acquisitions. The company aims to capitalize on the evolving digital landscape where authenticity and intent are paramount [33]

Core Viewpoint - Cloudflare, Inc. plans to launch "NET Dollar," a U.S. dollar-backed stablecoin aimed at facilitating instant and secure payments for autonomous AI agents operating on the web [1]. Group 1: Product Overview - NET Dollar is positioned as financial infrastructure for the "agentic web," where software agents manage transactions on behalf of users [1]. - The stablecoin is designed to support pay-per-use and microtransactions at an Internet scale [2]. - It aims to enable quick settlement, global operation, and interoperability with existing financial systems, allowing for automatic transactions by agents, developers, and creators [3]. Group 2: Business Model Shift - The introduction of NET Dollar reflects a shift from traditional Internet business models reliant on ad platforms and bank transfers to a model focused on pay-per-use, fractional payments, and microtransactions [4]. - This new model is intended to incentivize original and creative content that adds value [4]. Group 3: Technological Contributions - Cloudflare is working on modernizing financial infrastructure to facilitate rapid money movement, contributing to open payment standards for machine-to-machine transactions [5]. - The company is involved in the x402 foundation to standardize Internet payment interactions, expanding its focus from security and performance to payments infrastructure for AI-driven services [6]. - This initiative aligns with a broader industry trend towards compensating content creators and API providers through granular and programmable usage-based payments [6].

Executive Summary - Despite $30–40 billion in enterprise investment into GenAI, 95% of organizations are seeing zero return, leading to the phenomenon termed the GenAI Divide [6][12] - Only 5% of integrated AI pilots are generating significant value, while the majority fail to impact P&L [6][12] - The divide is attributed not to model quality or regulation, but to the approach taken by organizations [6][8] Adoption and Transformation - Over 80% of organizations have explored or piloted tools like ChatGPT, but these primarily enhance individual productivity rather than P&L performance [7][12] - 60% of organizations evaluated enterprise-grade systems, but only 20% reached pilot stage and just 5% reached production [7][12] - Most implementations do not lead to headcount reduction, but organizations crossing the divide see selective workforce impacts in specific functions [12][33] Industry-Level Transformation - Only two out of eight major sectors (Tech and Media) show meaningful structural change due to GenAI, while seven sectors remain stagnant [10][15] - A composite AI Market Disruption Index was developed to quantify disruption across industries, revealing limited transformation despite high investment [17][22] Pilot-to-Production Rates - The GenAI Divide is most evident in deployment rates, with only 5% of custom enterprise AI tools reaching production [24][28] - Generic LLM chatbots have high pilot-to-implementation rates (~83%), but this masks a deeper split in perceived value [29][30] - Enterprises with over $100 million in annual revenue lead in pilot count but report the lowest rates of pilot-to-scale conversion [32] Investment Patterns - 50% of GenAI budgets are allocated to sales and marketing, despite back-office automation often yielding better ROI [40][41] - The focus on visible functions over high-ROI back-office opportunities perpetuates the GenAI Divide [40][46] Learning Gap - The primary barrier to scaling is a learning gap; most GenAI systems do not retain feedback or adapt to context [8][48] - Users prefer consumer-grade tools like ChatGPT for simple tasks but abandon them for critical workflows due to lack of memory and customization [48][61] Successful Strategies - Organizations crossing the GenAI Divide build adaptive systems that learn from feedback and integrate deeply into workflows [71][75] - Successful vendors focus on narrow, high-value use cases and prioritize customization over broad feature sets [73][75] Buyer Practices - Successful organizations treat AI vendors as business service providers, demanding deep customization and holding them accountable to business metrics [96][108] - External partnerships with learning-capable tools see a deployment success rate of ~67%, compared to ~33% for internal builds [96][100] Workforce Impact - GenAI is starting to impact workforce dynamics, particularly in customer support and administrative functions, but not through widespread layoffs [112][114] - Organizations crossing the divide report measurable savings from reduced external spending rather than significant internal headcount reductions [110][116] Future Trends - The emergence of an Agentic Web, where autonomous systems can coordinate across the internet, represents the next evolution beyond the current GenAI Divide [121][123] - Organizations that quickly adopt learning-capable tools will establish competitive advantages as the window to cross the divide narrows [89][127]

Core Insights - Pinterest's CEO Bill Ready described the platform as an "AI-enabled shopping assistant," but believes the concept of an agentic web where AI shops on behalf of users is still a long way off [1][3] Company Positioning - Pinterest positions itself at the early stages of the shopping journey, where users seek ideas that may lead to purchases, raising concerns that AI could redirect users to personalized recommendations instead of using Pinterest [2] AI Integration - The company referred to the current exploration of AI-driven experiences as a "Cambrian moment," highlighting its use of AI for recommendation systems, multimodal AI, visual search, conversational search, and advertising efficiencies [5] User Experience - Ready emphasized that Pinterest's proactive recommendations resonate with users, who feel that "Pinterest just gets me," akin to a personal shopping assistant [4] User Concerns - There are growing user concerns regarding the prevalence of AI-generated low-quality content on Pinterest, leading to the introduction of tools to label AI-generated images and filter out such content [8] Talent Acquisition - Pinterest aims to attract AI talent focused on using AI responsibly and positively, distinguishing itself from other social media platforms [9] Financial Performance - Pinterest reported Q2 revenue of $998 million, exceeding expectations, but earnings per share of 33 cents fell short of the anticipated 35 cents, leading to a drop in stock price [10]

Core Concept - The article discusses the emergence of the "Agentic Web," a new paradigm in internet usage where AI agents autonomously complete tasks based on user-defined goals, marking a significant evolution from traditional web interactions [1][3]. Group 1: Evolution of the Web - The internet has undergone three major paradigm shifts over the past thirty years: from a keyword-driven "directory web" in the PC era, to a recommendation-driven "content explosion" in the mobile era, and now to an "action network" driven by AI agents [5][9]. - In the PC Web era, users actively searched and clicked through static pages, while in the Mobile Web era, users became consumers of algorithmically recommended content [7][8]. - The Agentic Web represents a shift where AI agents execute tasks autonomously, transforming the web from a static information repository to a dynamic ecosystem of actionable resources [9][10]. Group 2: Definition and Structure of Agentic Web - The Agentic Web is defined as a distributed, interactive internet ecosystem where AI agents, powered by large language models (LLMs), continuously plan, coordinate, and execute goal-oriented tasks [11][13]. - Users interact with the web by delegating tasks to AI agents, which can autonomously manage complex processes such as travel planning or data retrieval [13][15]. Group 3: Core Dimensions of Agentic Web - The structure of the Agentic Web can be understood through three core dimensions: intelligence, interaction, and economy [16]. - AI agents must possess cognitive abilities, including context understanding, long-term planning, and adaptive learning, to function effectively within this new paradigm [17]. - The interaction dimension emphasizes semantic-based communication between agents, allowing for collaborative task execution and negotiation [18]. - The economic dimension introduces the concept of "Agent Attention Economy," where the focus shifts from human clicks to AI agent interactions, leading to new advertising and service models [19][20]. Group 4: Application Scenarios - The Agentic Web enables three primary types of tasks: transactional (e.g., booking flights), informational (e.g., generating research summaries), and communicational (e.g., multi-agent negotiations) [20][21]. - In transactional scenarios, users can simply state their needs, and AI agents will autonomously complete the necessary steps, enhancing efficiency [22]. - Informational agents act as continuous research assistants, tracking developments in specific fields and synthesizing information over time [24]. - Communicational capabilities allow agents to collaborate and negotiate with one another, forming complex systems that can manage tasks across different domains [26]. Group 5: Challenges and Future Considerations - The implementation of the Agentic Web faces several systemic challenges, including enhancing AI capabilities, restructuring network infrastructure, and redefining economic models [28]. - Key challenges include improving multi-step reasoning, managing memory and context, ensuring tool security, and developing effective learning mechanisms [29][30][32][34]. - The need for unified communication protocols and decentralized trust systems is critical for enabling effective collaboration among AI agents [37][38]. - The shift towards the Agentic Web may disrupt traditional advertising models and labor markets, necessitating new business strategies and social considerations [47][49]. Group 6: Conclusion - The Agentic Web signifies a transformative shift from a passive information space to an active action space, where AI agents play a central role in executing tasks and creating value [50]. - This paradigm shift not only enhances efficiency but also redefines the relationship between humans and machines, as well as the economic structures of the internet [51].

Core Viewpoint - The article discusses the emergence of the "Agentic Web," a new paradigm in internet usage where AI agents autonomously complete tasks based on user-defined goals, marking a significant shift from traditional web interactions [3][6][57]. Group 1: Paradigm Shifts in the Web - The internet has undergone three major paradigm shifts: from a keyword-driven "directory web" in the PC era, to a recommendation-driven "content explosion" in the mobile era, and now to an "action network" driven by AI agents [8][9][15]. - In the Agentic Web, the role of the web transitions from being an information repository to an ecosystem of actionable resources for AI agents [13][15]. Group 2: Definition and Structure of Agentic Web - The Agentic Web is defined as a distributed, interactive ecosystem where AI agents, powered by large language models (LLMs), continuously plan, coordinate, and execute goal-oriented tasks [16][17]. - Users interact with the web by delegating tasks to AI agents, which autonomously handle the execution of these tasks [20][21]. Group 3: Core Dimensions of Agentic Web - The structure of the Agentic Web can be understood through three core dimensions: intelligence, interaction, and economy [24][28]. - The "Agent Attention Economy" signifies a shift in focus from human clicks to AI agent interactions, changing the metrics of commercial competition [29]. Group 4: Application Scenarios - The capabilities of the Agentic Web can be categorized into transactional, informational, and communicational tasks, enabling AI agents to perform a wide range of functions from booking tickets to conducting research [30][31]. - In transactional tasks, users can simply state their needs, and AI agents will autonomously complete the entire process, enhancing efficiency [33]. Group 5: Challenges Ahead - The implementation of the Agentic Web faces systemic challenges, including the need for improved AI capabilities, robust network infrastructure, and a redefined economic model [42][43]. - Key challenges include ensuring the reasoning and memory capabilities of AI agents, managing security risks associated with external tools, and establishing effective communication protocols for multi-agent collaboration [44][51]. Group 6: Socio-Economic Implications - The rise of the Agentic Web poses significant implications for traditional advertising models, labor markets, and economic structures, necessitating a reevaluation of how value is created and distributed in the digital economy [56][58]. - As AI agents become more prevalent, there is a pressing need to address the potential displacement of jobs and ensure equitable economic benefits [56][58].

Financial Data and Key Metrics Changes - Cloudflare achieved an annual run rate revenue exceeding $2 billion, with quarterly revenue of $512.3 million, reflecting a 28% year-over-year growth, up from 26.5% in the first quarter [5][24] - The company reported a gross margin of 76.3%, consistent with its long-term target range of 75% to 77% [6][28] - Operating income was $72.3 million, representing a 27% increase year-over-year, with an operating margin of 14.1% [31] Business Line Data and Key Metrics Changes - The number of customers paying over $100,000 annually increased by 22% year-over-year, totaling 3,712 customers [6][26] - Revenue contribution from large customers grew to 71% of total revenue, up from 67% in the same quarter last year [6][26] - Dollar-based net retention rate improved to 114%, up 3% quarter-over-quarter [6][27] Market Data and Key Metrics Changes - The U.S. market accounted for 49% of total revenue, increasing by 22% year-over-year, while EMEA represented 28% of revenue with a 29% increase, and APAC represented 15% with a 44% increase [25][26] - The total number of paying customers reached approximately 266,000, marking a 27% year-over-year increase [26] Company Strategy and Development Direction - Cloudflare is focusing on reaccelerating growth through innovation and operational efficiency, with a strong emphasis on large enterprise customers and expanding its sales capacity [5][24] - The company is positioning itself to capitalize on the shift from traditional web models to AI-driven business models, particularly in the publishing sector [20][21] - Cloudflare is developing its product offerings into distinct acts, with Act Four focusing on enabling transactions in an AI-driven web [22] Management's Comments on Operating Environment and Future Outlook - Management expressed confidence in the company's ability to maintain growth momentum, driven by strong performance in large customer segments and ongoing innovation [24][34] - The management highlighted the strategic importance of partnerships with media and AI companies to adapt to changing market dynamics [20][21] Other Important Information - Cloudflare issued $2 billion in convertible senior notes due in 2030, enhancing its financial flexibility [32] - The company ended the quarter with $4 billion in cash and equivalents, indicating a strong liquidity position [32] Q&A Session Summary Question: Insights on the business model for the Agentic web - Management indicated that various business models will likely emerge, emphasizing the need for a level playing field in content access and monetization [37][40] Question: Discussion on Act One products and their performance - Management highlighted the architectural advantages of Cloudflare's network, which allows for efficient handling of DDoS attacks without increasing costs [46][50] Question: Update on large deal momentum and partner growth - Management noted that the go-to-market strategy has shifted to a partner-first approach, which is driving growth in larger deals [60][62] Question: Media sector's attractiveness and Cloudflare's strategy - Management discussed the strategic importance of media partnerships and the potential for free services to create long-term value [75][76] Question: Relationship with foundation model vendors - Management confirmed that a significant portion of major AI companies are Cloudflare customers, utilizing its security and inference capabilities [80][82]

Investment Rating - The investment rating for the company is maintained as BUY with a target price of USD 564.57, indicating a potential upside of 20% from the closing price of USD 470.38 as of June 6, 2025 [1][8]. Core Insights - The company is leveraging its enterprise capabilities and Azure product advantages to establish a foundational platform for the Agentic Web, which is expected to accelerate the development of Agent applications and increase AI inference demand for its cloud business [1][2]. - The company has completed the infrastructure for Agentic Web development, focusing on both edge and cloud-side toolchains, which enhances development capabilities and supports third-party integrations [2]. - The cloud business has shown strong growth, with Azure and other cloud services revenue increasing by 33% year-over-year in 3QFY25, driven by AI contributions [3]. - The commercialization of AI applications in the US is accelerating, with strategic collaborations between the company and software vendors like SAP and ServiceNow enhancing cloud service reliance [4]. - Earnings forecasts project revenue growth for FY25E/FY26E/FY27E at USD 278.8 billion, USD 320.2 billion, and USD 368.8 billion respectively, with EPS expected to rise to USD 13.77, USD 16.12, and USD 18.85 [5]. Summary by Sections Development and Infrastructure - The company is enhancing its development capabilities with the launch of the GitHub Coding Agent and a complete enterprise-grade Agent customization system, which supports multi-Agent orchestration and flexible model selection [2]. - The introduction of Windows AI Foundry supports local Agent development, creating a more complete development ecosystem [2]. Financial Performance - The cloud business revenue growth of 33% year-over-year in 3QFY25 was significantly supported by AI, which contributed 16% to Azure's revenue growth [3]. - The company processed over 100 trillion tokens in 3QFY25, reflecting a fivefold increase year-over-year, indicating strong demand for AI inference [3]. Earnings and Valuation - The company maintains its earnings forecasts with projected revenues and EPS growth over the next three fiscal years, reflecting confidence in its competitive edge in AI and cloud business [5]. - The stock is valued at 41x FY25E PE, which is above the peers' average of 29.8x, justifying the BUY rating [5].

This article has been reviewed according to Science X's editorial process and policies . Editors have highlighted the following attributes while ensuring the content's credibility: Credit: CC0 Public Domain Microsoft sees artificial intelligence transforming the internet as fundamentally as mobile phones have over the past two decades. But the technology's limitations could curb Microsoft's grand vision. Generative AI—which creates content based on a user's request—burst into the zeitgeist in late 2022 w ...