Human-AgentOS

- Organizations are increasingly relying on both human workers and AI agents to execute business processes, yet existing systems are fragmented across recruiting platforms, workforce management tools, project management software, and AI applications. - Leaders lack visibility into who should perform a task, whether a task should be assigned to a human or an AI agent, how AI agents should be evaluated and selected, how mixed human-agent teams should collaborate, and how workforce productivity should be measured across both humans and AI. - A typical organization manually defines hiring or staffing requirements, searches for employees, freelancers, consultants, or service providers, discovers and evaluates AI tools and agents, assigns tasks across teams, coordinates workflows across departments, tracks project progress and outcomes, reviews work outputs, manages approvals and governance, and monitors performance and productivity. - As AI agents become part of the workforce, organizations must determine which tasks should be automated, decide when human oversight is required, evaluate AI agent capabilities and reliability, manage agent permissions and governance, coordinate human-agent collaboration, measure productivity across both humans and AI, and optimize cost, quality, and speed. - There is currently no unified platform that enables organizations to discover, deploy, manage, and optimize a workforce consisting of both human talent and AI agents.

- Access and manage the right capability in minutes instead of weeks. - Improve governance, permissions, approvals, and accountability for AI-agent work. - Create a practical path for AI agents and human specialists to be deployed together.

Work is split across recruiting platforms, workforce management tools, project management software and AI applications.