Naïve raises $28.5M to automate business setup with AI agents

A startup that promises to automate the administrative burden of launching and operating a business has closed a $28.5 million Series A round led by Nexus Venture Partners, according to TechCrunch.

Naïve provides infrastructure that enables AI agents to handle tasks ranging from LLC formation to setting up payment systems, email accounts, and cloud resources — all accessible through a single API. The company has attracted more than 30,000 developer customers since launch and scaled its annual run-rate revenue to the low double-digit millions over the past six months, a 10x increase, CEO Sean Dorje told TechCrunch.

How the platform works

Developers supply prompts to AI coding tools like Cursor or Claude Code, which connect to Naïve's APIs to provision business infrastructure. The system can orchestrate U.S. LLC formation by handling state selection, industry codes, business descriptions, and name registration, though human involvement remains necessary for KYC/KYB compliance and payments.

Once those steps are complete, AI agents can configure email inboxes, virtual cards, phone numbers, databases, computing resources, and integrations with services like Stripe and QuickBooks. A governance layer allows users to set budgets, restrict agent capabilities, and require human approval for sensitive actions. The company also offers templates for specific business types including AI SEO, SaaS applications, recruiting, and customer support.

Early use cases emerge

Dorje said customers are deploying Naïve to run AI automation agencies, autonomous content channels on TikTok and YouTube, and even a rental car agency. One customer operates a TikTok channel posting AI-generated videos of animals dancing and boxing. "The first business that a lot of people start is genuinely just selling agents to other small businesses," Dorje noted.

Tackling the cost problem

While business setup automation drove initial adoption, Naïve is now investing heavily in infrastructure to reduce the operational costs of running AI agents — expenses that can escalate quickly as agents call expensive models, pass large amounts of context between tasks, and consume resources while idle.

The company is building four key systems: a model router that directs queries to the most efficient model while preserving reasoned data; a memory system for storing and surfacing business context; an orchestrator for dividing work among agents; and a serverless runtime that runs agents in lightweight JavaScript environments rather than full virtual machines. This approach allows customers to pay primarily when agents are active.

"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. He added that enterprises are showing interest, though he declined to name specific companies.

Why it matters

The shift from setup automation to cost optimization signals a maturing market for AI agents in business operations. While developers may initially adopt Naïve to avoid administrative tedium, the recurring expense of operating multiple agents at scale could become the more valuable problem to solve — particularly for enterprises with established operations looking to deploy agent workforces efficiently.

Y Combinator, Zetta, Liquid 2, and angel investors including Gokul Rajaram, Apollo.io co-founder Tim Zheng, and former HubSpot COO JD Sherman participated in the round. The funding brings Naïve's total capital raised to approximately $32 million. The 10-person team plans to hire researchers and develop its infrastructure projects.

Details of the funding were first reported by TechCrunch.