SAN FRANCISCO, Calif., August 6, 2026 —Developers have long searched for ways to eliminate repetitive work, whether by writing scripts, creating automation tools, or adopting new programming methods. Artificial intelligence has accelerated that trend, allowing developers to generate software with minimal manual coding. Naïve is taking that idea beyond software development by offering infrastructure that allows AI agents to perform much of the work involved in establishing and operating a business.

The San Francisco-based startup has attracted more than 30,000 developers within months of launching its platform. Strong customer adoption, together with rapid revenue growth, has helped Naïve secure $28.5 million in Series A funding led by Nexus Venture Partners. The round also included participation from Y Combinator, Zetta, Liquid 2, and angel investors including Gokul Rajaram, Apollo.io co-founder Tim Zheng, and former HubSpot COO JD Sherman. Total funding now stands at roughly $32 million.

Moving Business Operations into AI Workflows

Naïve packages many of the administrative tasks required to launch a company behind a single API. Rather than manually creating email accounts, payment systems, phone numbers, databases, cloud resources, and financial software connections, developers can provide a prompt to coding tools such as Cursor, Claude Code, or Codex. Those tools interact with Naïve's infrastructure, allowing AI agents to complete much of the setup process automatically.

Business incorporation is also included. Users can instruct AI agents to form a U.S. limited liability company by providing information such as the preferred state of registration, industry classification, company description, and business name. Human participation remains necessary for identity verification, compliance procedures, and required payments, though much of the remaining administrative work can be completed by AI agents working through Naïve's platform.

Beyond company formation, the platform allows AI agents to create virtual payment cards, configure databases, establish computing resources, connect financial platforms such as Stripe and QuickBooks, and create communication channels. Governance controls allow users to establish spending limits, restrict what agents are permitted to do, and require approval before sensitive actions take place. Naïve also offers templates covering several business functions, including recruiting, accounting, customer service, AI search engine optimization, software-as-a-service applications, and mobile device emulation.

Rapid Customer Growth Draws Investor Interest

Customer adoption has accelerated rapidly since launch. According to Sean Dorje, CEO and co-founder, annual recurring revenue has grown tenfold during the past six months into the low double-digit millions. Much of that demand comes from developers using the platform to operate businesses that rely heavily on AI agents instead of large workforces.

Dorje said AI automation agencies currently represent one of the fastest-growing customer groups. Many developers establish businesses that create AI agents for small companies, using Naïve's infrastructure to automate administrative work while focusing their attention on customer acquisition and product development. Other customers have used the platform to operate online content businesses on TikTok and YouTube, while some have even automated parts of rental car operations.

Examples discovered by the company include AI-generated social media channels publishing animated animal videos without direct human involvement. Such use cases demonstrate how autonomous software is beginning to move beyond coding assistance into day-to-day business administration, where AI agents handle repetitive operational tasks while people supervise higher-level decisions.

Cutting the Cost of Running AI Agents

While automated business formation has attracted widespread attention, Naïve sees another opportunity in lowering the cost of operating AI agents over long periods. As businesses deploy more agents, computing expenses can grow rapidly because advanced language models consume significant processing power, repeatedly process large volumes of information, and remain active while waiting for new tasks.

Part of the newly raised capital will fund four infrastructure projects intended to reduce those expenses. The company is developing a model-routing system that directs requests to the most suitable AI model for each task while preserving previously generated reasoning. A dedicated memory layer will store business information so agents can retrieve relevant context without repeating the same processing steps. An orchestration system will divide work among multiple agents, allowing them to complete assignments more efficiently.

Naïve is also creating a serverless runtime that runs agents in lightweight JavaScript environments rather than assigning each agent a dedicated virtual machine. According to the company, this design allows customers to pay primarily when agents are actively performing work, reducing operating expenses for businesses deploying large numbers of autonomous systems.

Dorje said demand for inference optimization has grown rapidly because computing costs often become the largest ongoing expense for companies relying on AI agents. Lowering those costs allows developers and businesses to operate more agents without significantly increasing infrastructure spending. Enterprise organizations have also shown interest in these capabilities, although the company has not identified specific customers.

Image credit: Naïve

Funding Fuels Product Development

Naïve currently employs 10 full-time staff members and plans to expand its research capabilities following the Series A financing. Funding will be directed toward developing the company's infrastructure projects, including virtualized sandboxes for AI agents, inference optimization technology, the memory layer, and governance and orchestration capabilities.

The latest funding round reflects growing investor interest in software that supports autonomous AI operations rather than individual AI applications. Instead of creating another chatbot or coding assistant, Naïve provides the underlying systems that allow developers to launch businesses, connect essential services, manage operating resources, and coordinate AI agents from a unified platform.

Rapid adoption suggests developers are seeking ways to reduce the administrative burden associated with launching and operating companies. Business formation, financial software integration, communication tools, and cloud infrastructure traditionally require significant manual configuration before a company can begin serving customers. By allowing AI agents to complete much of that work, Naïve shortens the path from concept to operation while leaving compliance requirements and critical approvals under human supervision.

Future growth may depend less on business formation itself and more on reducing the long-term cost of autonomous operations. As organizations deploy more AI agents across customer service, accounting, recruiting, software development, and digital content production, efficient infrastructure could become just as valuable as the agents themselves. With fresh capital, a growing developer base, and expanding enterprise interest, Naïve is betting that the next stage of artificial intelligence will depend not only on smarter agents but also on the systems that allow them to operate efficiently at scale.