FinTech company Mercury has applied for a national bank charter with the Office of the Comptroller of the Currency (OCC) and for federal deposit insurance with the Federal Deposit Insurance Corporation (FDIC).By completing this form, you agree to receive marketing communications from PYMNTS and to the sharing of your information with our sponsor, if applicable, in accordance with our Privacy Policy and Terms and Conditions .Complete the form to unlock this article and enjoy unlimited free access to all PYMN ...

AI startups like OpenAI and Anthropic are notoriously capital intensive. But where does all that money go. Joining us now is Immad Akund, co-founder and CEO of Mercury, uh a fintech that offers bank-like services to many of those startups.So, uh Immad, uh interesting spot in the business here. Just set us up though and talk about exactly what your firm does, where you come into, uh the picture, I suppose, once these startups get funded. Yeah.Uh we started the company in 2017 and we provide radically differe ...

Core Insights - Startups are increasingly investing in AI tools to enhance economic growth, job creation, and opportunities, as highlighted by John Dearie, president of the Center for American Entrepreneurship [1] - A study by fintech firm Mercury revealed that over 70% of early-stage founders are increasing their AI and automation budgets [2] Group 1: Impact of AI on Startups - AI is transforming how startups operate by automating energy- and human-intensive tasks, allowing for greater efficiency [3] - Founders like Carolyn Pitt emphasize that AI tools facilitate core business functions such as sales, marketing, and operations, enabling teams to extend their capabilities [3] Group 2: Hiring Practices and Workforce Implications - The automation of time-intensive tasks may negatively affect hiring, particularly for entry-level positions, as startups prioritize capital efficiency [4] - Some startups are opting for AI over entry-level hires, leading to a reduction in traditional intern roles, as seen in Pitt's company [5] Group 3: Perspectives on AI and Employment - While concerns exist regarding AI replacing entry-level jobs, some view it as an opportunity for individuals to adopt entrepreneurial mindsets and develop new skills [6] - Startups are increasingly recognizing younger workers as valuable due to their familiarity with AI tools, which they use naturally in their daily lives [7]

Core Insights - Coinbase has launched a new business product called Coinbase Business, designed as an "all-in-one financial platform" for small- and medium-sized firms to manage crypto transactions and earn yield on stablecoins [1][3] - The platform will allow businesses to receive crypto, manage assets, and earn up to 4.1% APY on USDC held in their accounts [1][2] - Coinbase has a significant stake in USDC issuer Circle, allowing it to earn 50% of the revenue from interest on cash reserves backing the stablecoin [2] Product Features - Coinbase Business will offer instant crypto settlements, multi-user access, and integrations with accounting software like QuickBooks and Xero [1] - The onboarding process for Coinbase Business will be self-service, with most applicants approved within two days [3] - The platform aims to streamline financial operations, including payroll and vendor payments, and will link to crypto tax software [3] Market Position - The launch positions Coinbase in competition with fintech companies like Mercury and Brex, as well as crypto payment firms such as BitPay and OpenNode [4] - Coinbase is marketing the service as a "crypto operating account," combining banking, exchange, and payment processing functions [4] Development Timeline - The product is currently in its alpha phase, with businesses invited for early access, and full availability is planned for later in 2025 [5]

It’s been almost a decade since Omar Darwazah and Kyle Hendrick launched AAF Management and its first fund of $25 million in 2017. Rather than racing to dramatically increase their assets under management like many funds have in recent years, the partners have intentionally kept their fund sizes small, even as their reputation and returns have grown. Their latest vehicle — a $55 million early-stage hybrid fund, dubbed the Axis Fund, that recently closed — brings the Washington-based venture firm’s total ...

Core Insights - The report by a16z reveals that most funding in AI startups is directed towards API calls and high salaries for AI engineers rather than expensive model training [1][2] - AI is reshaping skills, tasks, and team structures, with large companies experiencing incremental improvements while startups are emerging as true AI-native companies [1][2] - The report identifies 50 AI-native application companies based on real spending data from 200,000 enterprise clients, highlighting a diverse range of applications [1][2] Group 1: Key Trends in AI Applications - Horizontal applications dominate the market, accounting for 60% of the list, with vertical applications making up 40% [2] - Notable horizontal applications include general-purpose large language model assistants like OpenAI and Anthropic, as well as intelligent work platforms such as Notion [2][3] - Creative tools have become the largest single category on the list, with ten companies, including Freepik and ElevenLabs, showcasing a shift from vertical to horizontal usage [3] Group 2: Vertical Applications and Workforce Transformation - Vertical AI applications are evolving along two paths: enhancing human capabilities and fundamentally reshaping job roles [4] - Among the 17 vertical application companies, 12 focus on human enhancement tools, while 5 provide end-to-end "AI employee" solutions [4] - Key vertical sectors include customer service, sales and marketing, and human resources, with companies like Lorikeet and Micro1 leading the way [4] Group 3: Emergence of Ambient Coding - The emerging field of "ambient coding" has successfully transitioned from consumer markets to enterprise workflows, with companies like Replit leading the charge [5] - Replit generates significantly higher revenue from enterprise clients compared to its competitors, indicating its strong market position [5] - The future of ambient coding may see fragmentation with the rise of various application development platforms [5] Group 4: Product Evolution from Personal to Enterprise Solutions - Nearly 70% of the companies on the list support individual users and promote team collaboration without requiring enterprise licenses [6] - Many companies started by serving individual users and gradually expanded to team and enterprise functionalities, reflecting a shift in AI product development [6] - The trend indicates that consumer-grade AI products are increasingly meeting enterprise needs, leading to rapid adoption in workplace settings [6][7]

Core Insights - CodeRabbit, an AI-driven code review startup, has raised $60 million in Series B funding, achieving a valuation of $550 million [4] - The company was founded in early 2023 by Harjot Gill, who identified a bottleneck in code review processes due to the rise of AI code generation tools [2][3] - CodeRabbit's monthly business growth rate is 20%, with an annual recurring revenue (ARR) exceeding $15 million [4] Company Overview - CodeRabbit helps over 8,000 companies, including Chegg, Groupon, and Mercury, save time on code reviews, which have become increasingly time-consuming with the rise of AI-generated code [4] - The platform can understand enterprise codebases, allowing it to identify errors and provide feedback, effectively reducing the manpower needed for code reviews by half [4] Market Position and Competition - CodeRabbit faces competition from other startups like Graphite and Greptile, as well as established AI coding assistants like Anthropic's Claude Code and Cursor [5] - Gill believes that customers will prefer independent solutions like CodeRabbit over bundled offerings due to its technical depth and breadth [5] User Adoption and Trends - Thousands of developers are willing to pay $30 per month for CodeRabbit's services, indicating a strong market demand [6] - Despite the popularity of AI code review tools, there remains a need for human intervention to fix issues in AI-generated code, leading to the emergence of roles such as "code cleanup specialists" [6]

Core Viewpoint - The article argues that the current approach to promoting competition in electricity markets may be misguided, as it overlooks the complexities of market dynamics and the need for stable long-term contracts to foster genuine competition and investment [1][10][13]. Group 1: Competition Dynamics - Politicians often advocate for increased competition as a solution to rising electricity prices, but this may only provide temporary relief [2][4]. - Encouraging retail competition is prioritized, yet consumer inertia in switching retailers limits its effectiveness, which is seen as a barrier to competition [2][3]. - Standalone retailers face challenges in accessing generation from gentailers on fair terms, which hampers their ability to compete effectively [3][4]. Group 2: Gentailers vs. Standalone Retailers - Gentailers, which combine generation and retailing, have advantages that standalone retailers lack, particularly in managing investment risks and pricing [6][16]. - The separation of generation and retailing is argued to be detrimental to achieving lower prices and better investment in the electricity market [7][16]. - Standalone retailers struggle to secure long-term contracts with generators due to the risk of losing customers to cheaper competitors, leading to a lack of viable investment [9][12]. Group 3: Proposed Solutions - To enhance competition, the article suggests making it more difficult for customers to switch retailers during periods of falling wholesale prices, potentially through long-term retail contracts [10][14]. - New retailers should either be gentailers or have long-term supply contracts with generators to ensure stability and reduce the risk of hit-and-run competition [11][12]. - By addressing the uncertainty in long-term contracts, both generators and retailers can benefit, leading to more credible competition and ultimately benefiting consumers [13][14].

RT Patrick Collison (@patrickc)Introducing @Tempo.At Stripe, we care about high-throughput, low-latency payments use cases. As the use of stablecoins (and crypto more broadly) grows across Stripe, Bridge, and Privy, we found that existing blockchains are not optimized for them.For example, it's valuable for real-world financial applications that fees be denominated in a fiat currency that makes sense to the user, but existing blockchains denominate their fees in blockchain-specific tokens. Batch transfers a ...

Core Insights - Campfire, an AI accounting startup, completed a $35 million Series A funding round led by Accel, with participation from Foundation Capital, Y Combinator, Capital 49, and angel investor Dan Kang [1][2] - The company aims to disrupt legacy ERP accounting software like NetSuite by automating tedious financial tasks using LLM-driven solutions [2][3] - Campfire has already attracted around 100 clients, including a global client with an annual recurring revenue (ARR) nearing $250 million, demonstrating its competitive potential in the market [2] Funding and Market Potential - Accel partner John Locke was impressed by the willingness of large enterprises to trust a seed-stage startup with their entire ERP systems, which influenced his decision to lead the funding round [3] - The ERP software market is projected to reach $56 billion in total size by 2024, highlighting the significant market opportunity for AI-enabled ERP solutions [3]