Lua Secures $5.8M Seed Round to Launch AI Operating System for Human-Agent Collaboration

The Shift to Hybrid Workforces

Lua, the London-based startup building an operating system for human-agent collaboration, announced a $5.8 million Seed round today. The funding was led by Norrsken22, with participation from Flourish Ventures, 20VC, and Y Combinator. This investment aims to accelerate the deployment of AI workforces across global markets. Founded by Lorcan O'Cathain and Stefan Kruger, the platform provides a full-stack environment for managing AI agents as if they were members of an org chart. The duo met while scaling fintech operations in East Africa and saw a need for better orchestration between humans and machines. Their vision moves beyond simple workflow automation into a comprehensive management layer.

Empowering Technical and Non-Technical Teams

The technology serves both technical and non-technical teams through a unified interface. Developers can use a command line interface and TypeScript for deep customization, while business operators utilize natural language to manage agent behavior. This approach ensures that companies own their logic and outcomes rather than relying on black-box tools. Lua plans to use the capital to expand its developer community and its global Implementation Network. This network consists of independent partners who deploy tailored agent workforces in local markets across Africa, Asia, Europe, and the US. By scaling these partnerships, the company hopes to lower the barrier for mid-market enterprises to adopt AI.

Rapid Market Adoption

Growth has been rapid since the platform launched its developer tools in late 2025. The company reports revenue growth of 30 percent week-on-week and achieved one million dollars in annual recurring revenue within three months. In February 2026, the platform saw more agents created than in all previous months combined. While competitors like Zapier or traditional point-automation tools focus on task triggers, Lua targets the underlying infrastructure and monitoring. The company rejects per-outcome pricing models that often penalize businesses for their own success. Instead, it offers a predictable framework where efficiency compounds over time as agents improve.