Naïve, a startup building infrastructure that lets AI agents automate business setup and operations, has raised $28.5 million in a Series A funding round led by Nexus Venture Partners. The company says its platform can handle most of the drudgery involved in launching and running a company, from incorporation to payments to cloud infrastructure.
The funding arrives just months after Naïve launched, and the startup already claims more than 30,000 developer customers. Over the past six months, Naïve has scaled its annual run-rate revenue by 10x to the low double-digit millions. Total capital raised now stands at roughly $32 million, including the new round.
From vibe-coding to autonomous companies
Developers have long hated boring tasks. Vibe-coding already lets them skip most of the work in building products. Naïve takes that idea further, aiming to automate the operations side of a business entirely.
The company packages payments, email accounts, phone numbers, cloud infrastructure, storage, and company incorporation behind a single API. A developer can give a prompt to tools like Cursor, Claude Code, or Codex, and those tools connect to Naïve's API to do the rest.
Naïve's agents can orchestrate the formation of a U.S. LLC, including selecting the state, industry code, business description, and proposed names. Humans still have to step in for KYC and KYB processes, and they must make required payments. But AI can set up email inboxes, virtual cards, phone numbers, databases, computing resources, and connections to services like Stripe and QuickBooks.
The platform includes a governance layer for setting budgets, restricting what agents can do, and requiring human approval for sensitive actions. Naïve also provides templates for businesses such as AI SEO, full-stack SaaS apps, recruiting, accounting, customer support, and a mobile emulator.
Customers running real businesses on AI
Sean Dorje, CEO and co-founder of Naïve, said customers are already using the platform to run autonomous businesses. Some operate "face-less" online content channels on TikTok and YouTube. One customer runs a TikTok channel posting AI-generated videos of cats and dogs dancing and boxing.
"I think the one that's growing the fastest right now is AI automation agencies," Dorje said.
Those agencies are the fastest growing customer segment, he added. They sell AI services to other small businesses, and they use Naïve to handle their own back office.
"You know, the first business that a lot of people start is genuinely just selling agents to other small businesses […] We have some customers who run an entire rental-car agency autonomously," Dorje said.
The rental-car agency example shows how far the platform can go. Dorje did not name the customer, but he said the entire operation runs without human staff managing day-to-day tasks.
The real money may be in cutting agent costs
The toolkit for running businesses may only be part of Naïve's opportunity. Keeping AI agents running can get expensive fast. Models are costly, context windows grow large, and idle resources waste money.
Naïve is building a serverless runtime that runs agents in lightweight JavaScript environments instead of complete virtual machines. That approach lets customers pay primarily when an agent is active, rather than for always-on infrastructure. A customer who previously paid $330 a month for a full virtual machine might now pay as little as $1.28 per active hour, and in some cases just $1 for a short task, Dorje said.
"Part of running an autonomous company and running agents, like that's your biggest cost line now, and so the highest growing demand right now, I would say is [for] inference and serverless agents," Dorje said.
Optimizing inference costs is one of Naïve's fastest growing sources of demand, he said. The company is developing a model router to send queries to the most efficient model for each task. It is also building a memory system to store and surface business context, plus an orchestrator for dividing work among agents.
Enterprises may find value in reducing the recurring costs of operating agents. Naïve's infrastructure business is getting interest from enterprises, though Dorje did not name any. The company currently has 10 full-time employees.
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What the new funding will build
The Series A proceeds will be used to hire researchers and develop four infrastructure projects: virtualized sandboxes for agents, model routing and inference optimization, a memory layer, and governance and orchestration.
Y Combinator, Zetta, and Liquid 2 participated in the round. Angel investors Gokul Rajaram, Tim Zheng, and JD Sherman also joined. Zheng is a co-founder of Apollo.io, and Sherman is the former COO of HubSpot.
Naïve's pitch is simple: developers should not have to manage the boring parts of a business. The company claims its infrastructure can automate most of the work in setting up and running a company. With 30,000 developers already on board, the market seems to agree.
The challenge ahead is scale. Naïve has only 10 employees, and it is taking on ambitious infrastructure projects. The company will need to hire carefully and ship quickly to keep its early momentum.
Developers may initially use Naïve for setup, but they may care more about reducing recurring costs as they grow. That shift could make inference optimization a more valuable business than helping founders incorporate. Naïve is betting on both.
The company's serverless runtime is a key differentiator. Running agents in lightweight JavaScript environments instead of full virtual machines cuts costs dramatically. Customers pay only when an agent is active, which keeps bills predictable.
Naïve's governance layer also addresses a real concern. Agents with too much freedom can cause damage. Budgets, capability restrictions, and human approval requirements give customers control.
The templates Naïve provides cover common business types. AI SEO, full-stack SaaS apps, recruiting, accounting, customer support, and a mobile emulator are all available out of the box. That lowers the barrier for non-technical founders.
The customer running a TikTok channel with AI-generated animal videos shows the range of use cases. Content channels on TikTok and YouTube can run with minimal human oversight, and Naïve handles the infrastructure.
The rental-car agency example is more complex. Running a fleet, managing bookings, and handling payments all require coordination. Naïve's orchestrator divides work among agents to handle such tasks.
Naïve's model router is another piece of the puzzle. Different tasks need different models, and sending everything to the most powerful model wastes money. The router picks the most efficient option for each query.
The memory system stores business context so agents do not have to re-learn everything on each interaction. That reduces token usage and improves consistency.
Naïve's governance and orchestration projects are still in development. The company has not shared a timeline for when they will ship.
The funding round gives Naïve runway to build. With $28.5 million in new capital and roughly $32 million raised in total, the company has resources to hire researchers and expand its team.
The 10x revenue growth over six months is notable, but the base was small. The low double-digit millions in annual run-rate revenue is a start, not a finish.
Naïve's bet is that AI agents will run more and more of the economy's boring work. If that happens, the infrastructure layer becomes essential. The company wants to be that layer.