Na#ve raises $28.5M to automate business operations

AI agent infrastructure startup Naïve has secured $28.5 million in a Series A funding round led by Nexus Venture Partners, bringing its total raised capital to approximately $32 million. The round also saw participation from Y Combinator, Zetta, Liquid 2, and prominent angel investors including Gokul Rajaram, Apollo.io co-founder Tim Zheng, and former HubSpot COO JD Sherman. With a lean team of 10 full-time employees, the company plans to use the capital to hire researchers and advance four core infrastructure projects: virtualized sandboxes, model routing, a memory layer, and governance orchestration.

Naïve aims to eliminate the administrative friction of launching a business by consolidating payments, email, phone numbers, cloud hosting, and corporate incorporation behind a single API. Developers can feed a prompt to AI coding assistants like Cursor, Claude Code, or Codex to connect with Naïve's API and automatically provision this infrastructure. The platform can orchestrate U.S. LLC formation, set up Stripe and QuickBooks integrations, and deploy virtual cards, though human intervention is still required for KYC/KYB compliance and payments. This approach has attracted over 30,000 developer customers, helping Naïve scale its annual run-rate revenue tenfold into the low double-digit millions over the last six months.

For AI practitioners, Naïve addresses the massive operational costs associated with running autonomous agent loops. To prevent agents from draining token budgets through idle virtual machines and redundant model calls, Naïve is developing a serverless runtime that executes agents in lightweight JavaScript environments. It is also building a model router to direct queries to the most cost-effective models, a memory system to preserve business context, and an orchestrator to delegate tasks. According to CEO Sean Dorje, while the setup toolkit is highly popular, optimizing inference and deploying serverless agents represents their fastest-growing area of demand.