From One-Person Companies to Generative Media, AI Funding Spans the Stack

Ever since generative artificial intelligence entered the mainstream, one of its most provocative promises has been the idea that a single person could run a billion-dollar company

The General Intelligence Company of New York is building toward that vision. The startup announced this month that it raised $8.7 million in seed funding to develop agent-based systems designed to take over large portions of company operations, moving the idea of a one-person enterprise from theory toward execution.

The company’s name deliberately evokes Gilded Age ambition, and founder Andrew Pignanelli told PYMNTS that the reference was intentional. He said he views AI as foundational infrastructure for the next era of company-building, much as railroads and industrial capital reshaped the United States economy more than a century ago. General Intelligence’s flagship product, Cofounder, is designed to let individuals operate companies by delegating execution to coordinated AI agents rather than human teams.

The company began by working backward from what Pignanelli called the one-person billion-dollar business.

“We started at the end, the actual one-person billion-dollar company, and worked our way back and we were like, ‘What can we do today?’” he said.

Rather than embedding AI into isolated workflows, the goal is to create systems where a human functions like a CEO while coordinated AI agents handle execution across engineering, marketing, operations and customer support.

At the lowest level, many individual contributor tasks are already approaching full automation, Pignanelli said. Code generation, design and marketing execution have advanced rapidly, with systems now nearing the ability to generate and deploy production-ready code without breaking live environments. What remains unsolved are the higher-order problems that distinguish real companies from task automation.

“What is not there is coordination and memory systems,” he said, adding that AI still lacks the ability to maintain a durable understanding of how a business operates over time or to manage groups of agents the way people manage teams.

By automating non-differentiating work, AI could lower barriers to entrepreneurship as productivity gains and automation reshape labor markets, he said.

With fresh capital and growing attention on agent-based systems, General Intelligence is pushing toward what Pignanelli described as the first fully autonomous company. He said the company is sprinting toward that milestone, and it could emerge in the first half of 2026.

Other Funding Activity

Retail data intelligence firm Crisp raised $26 million in a Series B1 round to expand its AI solutions for retailers and consumer packaged goods brands. The company operates in a part of the retail stack where fragmented data across suppliers and retailers often leads to inventory mismatches, forecasting errors and strained relationships. By reconciling data from multiple systems, Crisp aims to give brands and retailers a more reliable view of demand and stock levels as omnichannel fulfillment grows more complex and margins remain under pressure.

Enterprise automation startup Serval raised $75 million in a Series B funding round led by Sequoia Capital, valuing the company at $1 billion. Serval builds AI agents that handle routine internal work across IT, HR, legal and finance. As enterprises look to move generative AI beyond individual productivity tools, Serval’s approach reflects demand for systems that can execute work directly inside existing enterprise environments.

Infrastructure investment is also adapting to operational demands. Real-time generative media startup Fal raised $140 million in a Series D round led by Sequoia Capital, with participation from Kleiner Perkins, Alkeon Capital and Nvidia’s NVentures. The company focuses on low-latency image and video generation, supporting applications where AI outputs must be delivered instantly rather than offline. As generative AI increasingly appears in customer-facing products, inference performance and responsiveness are becoming central to user experience.

Prime Security raised $20 million in a Series A round to expand its agentic security platform, embedding autonomous security checks directly into development workflows. Faster release cycles and increased use of AI-generated code have made traditional, manual security reviews harder to scale, pushing enterprises to integrate security without slowing delivery.

Conversational AI company PolyAI raised $86 million to expand its enterprise voice assistant platform, targeting industries where accuracy, reliability and compliance are critical. As contact centers remain among the most labor-intensive enterprise functions, the funding reflects continued interest in AI systems that can resolve more inquiries end-to-end without human intervention.

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