Naïve Raises $28.5 Million to Automate Company Incorporation
According to an exclusive report by TechCrunch, startup company Naïve has raised $28.5 million in a Series A funding round to completely automate the tedious tasks of setting up and running a business. The new funding, which was led by Nexus Venture Partners, brings the company's total capital raised to approximately $32 million. Naïve offers technological infrastructure that allows artificial intelligence agents (AI Agents) to take on the bulk of the work involved in running a business, and has already registered over 30,000 developer customers within just a few months of its launch.
Unified Infrastructure for Company Incorporation and Management
The company claims that its infrastructure is capable of automating most of the work involved in setting up and managing a business, provided that the user supplies the artificial intelligence agents and the required token budget. The platform consolidates the complex processes of connecting payment systems, email accounts, phone numbers, cloud infrastructure, storage, and company incorporation behind a single unified API.
Naïve provides a prompt that developers can feed into popular tools like Cursor, Claude Code, or Codex. These tools connect to the company’s APIs to allocate and deploy the necessary infrastructure to set up the business. The system allows an AI agent to orchestrate the founding process of a U.S. Limited Liability Company (LLC), providing specific details such as the state where the company will be registered, its industry code, the business description, and proposed names. At the same time, human users are still required to be actively involved to complete identity verification and compliance processes (KYC/KYB) and to make the necessary payments.
The rest of the setup process can be performed entirely by AI agents. This includes setting up email inboxes, virtual cards, phone numbers, databases, computing resources, and connecting to popular services such as Stripe and QuickBooks. To ensure oversight, Naïve offers a governance layer that promises to help users set budgets, restrict their agents' capabilities, and require human approval before sensitive actions are executed. Additionally, the company provides pre-built templates for various types of businesses, such as AI-driven SEO agencies, full-stack SaaS applications, recruiting businesses, accounting, customer service, and even a mobile device emulator through which AI agents can operate smartphone apps on simulated devices.
Rapid Growth and Diverse Real-World Use Cases
The appeal of these automation solutions has resonated widely, as evidenced by the company's expanding customer base. Naïve's CEO and co-founder, Sean Dorje, shared that the company has scaled its annual run-rate revenue (ARR) by 10x, reaching the low double-digit millions range over the past six months.
According to Dorje, customers are using Naïve's infrastructure to run completely autonomous businesses (Autonomous Businesses). Among the notable use cases are AI automation agencies, "faceless" online content channels on platforms like TikTok and YouTube, and even a car rental agency. In one instance, Dorje discovered that the company’s infrastructure was supporting a TikTok channel that publishes AI-generated videos featuring dancing and boxing cats and dogs.
The fastest-growing segment right now is AI automation agencies, Dorje noted in an interview with TechCrunch. Dorje explained that the first business many people set up is simply selling AI agents to other small businesses, adding that the company has clients who run an entire rental car agency completely autonomously using the system.
Tackling the Running Costs of AI Agents
While the concept of full automation sounds promising, the operational costs of active AI agents can quickly become astronomical. This is due to the fact that agents call expensive AI models and brands, pass massive amounts of context between different tasks, and consume costly computing resources even when they are in an idle or standby state.
To address this issue, Naïve is allocating a portion of the newly raised capital to develop dedicated infrastructure, which it claims can make agent operation loops far more efficient. The company is currently working on the development of four key infrastructure projects:
- Model Router: Its task is to send queries to the most efficient model for a given task, while preserving and replaying data that has already undergone reasoning and processing.
- Memory System: This stores and surfaces the required business context for agents at the exact moment they need it to perform their tasks.
- Orchestrator: Designed to distribute work optimally among several different agents.
- Serverless Runtime: Runs agents within lightweight JavaScript environments, instead of assigning a complete virtual machine (VM) to each agent. This approach allows customers to pay primarily when the agent is active and performing actual work, thereby significantly lowering the cost of deploying large quantities of agents simultaneously.
Dorje emphasized that optimizing inference costs is one of the company's fastest-growing sources of demand. Dorje explained that the cost of running agents currently represents the single largest cost line in managing an autonomous company, which is why the greatest demand at the moment is for inference and serverless agents solutions. He added that this part of the business is also generating significant interest from large enterprises (Enterprises), though he declined to name these organizations. This interest could turn out to be a much more valuable business than helping entrepreneurs set up phone numbers and corporate credit cards. Developers may initially use Naïve to overcome the tedious tasks of setting up a company, but as they grow, their primary interest will shift to whether the platform can significantly reduce the recurring fixed costs of operating a large number of agents.
Future Plans and Company Structure
Currently, Naïve employs ten full-time employees. Dorje stated that the proceeds from the Series A round will be used to hire researchers and develop the company's four infrastructure projects: virtualized sandboxes for agents, model routing and inference optimization, a memory layer, and governance and orchestration systems.
Prominent organizations and investors participated in this funding round, including Y Combinator, Zetta, Liquid 2, as well as private angel investors such as Gokul Rajaram, Apollo.io co-founder Tim Zheng, and former HubSpot COO JD Sherman. The participation of these leading industry figures underscores the potential inherent in agent-based automation for the next generation of digital businesses.