
Capchase has raised $200 million in a combination of equity and debt to fuel its expansion into the enterprise market. The New York-based company, which has shifted from revenue-based financing to a B2B buy now, pay later model, uses AI to automate and speed up traditionally slow financing processes. This pivot has resulted in a 400% growth rate over the past year. The new funds will help Capchase expand its operations globally, including a new entry into the Australian market.
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© Crunchbase NewsAnthropic has dramatically increased its standing in the AI sector by securing $65 billion in a Series H funding round, boosting its valuation to $965 billion. This development places Anthropic ahead of OpenAI in terms of valuation, marking a significant shift in the competitive dynamics of AI companies. The funding was led by major investors such as Altimeter Capital and Sequoia Capital, with Amazon also contributing. This substantial investment reflects the growing demand for Anthropic's AI tools like Claude, which are becoming essential for its expanding enterprise customer base. With this new capital, Anthropic is poised to enhance its capabilities and reach in the AI market.
© Crunchbase NewsEven with the rise in AI funding, Black startup founders are still receiving a minimal portion of venture capital. In 2025, Black-founded startups secured only 0.32% of U.S. venture funding, marking a significant decrease from earlier years. Companies like SambaNova, which raised $350 million in a Series E round, are exceptions rather than the norm. This situation highlights the ongoing challenges Black entrepreneurs face in accessing capital, despite their active use of AI technologies. Building strong networks and relationships is becoming increasingly vital for these founders to compete in the funding arena. While there are some positive developments, the overall funding environment remains difficult for Black founders.
© Crunchbase NewsVenture capitalists are increasingly investing in AI-native startups targeting traditionally 'uninvestable' sectors like defense, energy, and government. These industries, once avoided due to slow procurement and regulatory hurdles, are now seen as ripe for disruption thanks to AI advancements. The shift is driven by geopolitical and economic pressures, alongside the realization that AI can streamline complex processes and reduce migration times. This trend marks a significant opportunity for startups to challenge incumbents with AI-integrated solutions, potentially transforming foundational sectors of the global economy.
© SiftedHenrik Landgren, a former Spotify executive, is leveraging AI to help venture capitalists discern which startups are likely to succeed. By employing cohort analysis, Landgren's approach aims to identify startups that are not just hype. This method groups startups by shared characteristics to predict their potential success, offering a more data-driven approach to investment decisions. The initiative reflects a growing trend of using AI to bring more precision and objectivity to the venture capital industry. This could potentially shift how investments are made, focusing more on data-backed insights rather than intuition alone.
© SiftedInherent, a new AI lab founded by former DeepMind researchers, has secured $50 million in funding to develop 'AI-native science.' This approach aims to integrate human scientific inquiry with advanced AI systems to foster novel discoveries. The startup's platform, Faraday, seeks to address the limitations of current AI by identifying which scientific questions are worth pursuing. With backing from Index Ventures and Radical Ventures, Inherent is poised to explore the intersection of AI and scientific research, potentially transforming how breakthroughs are achieved.
© TechCrunch AIGlean has achieved a remarkable $300 million in annual recurring revenue, tripling its figures in just 15 months. This growth is particularly notable as the company faces new competition from tech giants like Google and Microsoft in the enterprise AI search market. Glean's edge lies in its 'context graph' technology, which enhances AI efficiency by reducing computing costs for enterprises. This feature is increasingly appealing to businesses aiming to manage their AI budgets more effectively. As the market becomes more crowded, Glean's ability to offer tailored AI solutions gives it a significant advantage. The company's revenue model, which includes both consumption-based and hybrid pricing, reflects its adaptability to client needs.