Nexent is a zero-code platform for auto-generating production-grade AI agents using Harness Engineering principles.
Nexent addresses the complexity of building and deploying AI agents by eliminating the need for orchestration logic or drag-and-drop interfaces. Instead, it uses natural language prompts to define agent behavior, automatically generating agents with unified tools, skills, memory management, and orchestration. The platform includes built-in constraints, feedback loops, and control planes to ensure agents operate safely and predictably in production environments.
Teams building AI agents should consider Nexent if they want to reduce development overhead and avoid manual orchestration work. The platform suits projects ranging from individual prototypes to team deployments, with Docker and Kubernetes deployment options supporting different infrastructure preferences. Docker deployment is recommended for individuals and small teams, while Kubernetes is available for larger-scale deployments. System requirements range from 4 CPU cores and 8 GiB memory for Docker to 4 cores and 16 GiB for Kubernetes, with recommended configurations providing better production performance.
The project receives issue reports from both core maintainers and external users, indicating adoption beyond the core team without creating an overwhelming support burden. Maintainers typically respond to new issues and pull requests within hours. Work in the issue tracker is dominated by high-priority and critical labels, reflecting active engagement with significant problems.
